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<li class="navelem"><a class="el" href="dir_39ef148c3cf3468c290ae8c03b3c03af.html">pcl</a></li><li class="navelem"><a class="el" href="dir_474708a720ff06817ce2c12e28baf137.html">common</a></li> </ul>
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<a href="centroid_8h.html">Go to the documentation of this file.</a><div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/*</span></div>
<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Software License Agreement (BSD License)</span></div>
<div class="line"><a name="l00003"></a><span class="lineno"> 3</span> <span class="comment"> *</span></div>
<div class="line"><a name="l00004"></a><span class="lineno"> 4</span> <span class="comment"> * Point Cloud Library (PCL) - www.pointclouds.org</span></div>
<div class="line"><a name="l00005"></a><span class="lineno"> 5</span> <span class="comment"> * Copyright (c) 2010, Willow Garage, Inc.</span></div>
<div class="line"><a name="l00006"></a><span class="lineno"> 6</span> <span class="comment"> * Copyright (c) 2012-, Open Perception, Inc.</span></div>
<div class="line"><a name="l00007"></a><span class="lineno"> 7</span> <span class="comment"> *</span></div>
<div class="line"><a name="l00008"></a><span class="lineno"> 8</span> <span class="comment"> * All rights reserved.</span></div>
<div class="line"><a name="l00009"></a><span class="lineno"> 9</span> <span class="comment"> *</span></div>
<div class="line"><a name="l00010"></a><span class="lineno"> 10</span> <span class="comment"> * Redistribution and use in source and binary forms, with or without</span></div>
<div class="line"><a name="l00011"></a><span class="lineno"> 11</span> <span class="comment"> * modification, are permitted provided that the following conditions</span></div>
<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="comment"> * are met:</span></div>
<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> <span class="comment"> *</span></div>
<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="comment"> * * Redistributions of source code must retain the above copyright</span></div>
<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> <span class="comment"> * notice, this list of conditions and the following disclaimer.</span></div>
<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="comment"> * * Redistributions in binary form must reproduce the above</span></div>
<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> <span class="comment"> * copyright notice, this list of conditions and the following</span></div>
<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="comment"> * disclaimer in the documentation and/or other materials provided</span></div>
<div class="line"><a name="l00019"></a><span class="lineno"> 19</span> <span class="comment"> * with the distribution.</span></div>
<div class="line"><a name="l00020"></a><span class="lineno"> 20</span> <span class="comment"> * * Neither the name of the copyright holder(s) nor the names of its</span></div>
<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> <span class="comment"> * contributors may be used to endorse or promote products derived</span></div>
<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="comment"> * from this software without specific prior written permission.</span></div>
<div class="line"><a name="l00023"></a><span class="lineno"> 23</span> <span class="comment"> *</span></div>
<div class="line"><a name="l00024"></a><span class="lineno"> 24</span> <span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS</span></div>
<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment"> * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT</span></div>
<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment"> * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS</span></div>
<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"> * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE</span></div>
<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"> * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,</span></div>
<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"> * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,</span></div>
<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"> * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;</span></div>
<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"> * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER</span></div>
<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT</span></div>
<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN</span></div>
<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"> * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE</span></div>
<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"> * POSSIBILITY OF SUCH DAMAGE.</span></div>
<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"> *</span></div>
<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00038"></a><span class="lineno"> 38</span>  </div>
<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#pragma once</span></div>
<div class="line"><a name="l00040"></a><span class="lineno"> 40</span>  </div>
<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor">#include <<a class="code" href="memory_8h.html">pcl/memory.h</a>></span></div>
<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="preprocessor">#include <<a class="code" href="pcl__macros_8h.html">pcl/pcl_macros.h</a>></span></div>
<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> <span class="preprocessor">#include <pcl/point_cloud.h></span></div>
<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="preprocessor">#include <pcl/type_traits.h></span></div>
<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> <span class="preprocessor">#include <pcl/PointIndices.h></span></div>
<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="preprocessor">#include <pcl/cloud_iterator.h></span></div>
<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="comment"></span> </div>
<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="comment">/**</span></div>
<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> <span class="comment"> * \file pcl/common/centroid.h</span></div>
<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> <span class="comment"> * Define methods for centroid estimation and covariance matrix calculus</span></div>
<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"></span> </div>
<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment">/*@{*/</span></div>
<div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="keyword">namespace </span><a class="code" href="namespacepcl.html">pcl</a></div>
<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> {<span class="comment"></span></div>
<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="comment"> /** \brief Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.</span></div>
<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> <span class="comment"> * \param[in] cloud_iterator an iterator over the input point cloud</span></div>
<div class="line"><a name="l00059"></a><span class="lineno"> 59</span> <span class="comment"> * \param[out] centroid the output centroid</span></div>
<div class="line"><a name="l00060"></a><span class="lineno"> 60</span> <span class="comment"> * \return number of valid points used to determine the centroid. In case of dense point clouds, this is the same as the size of input cloud.</span></div>
<div class="line"><a name="l00061"></a><span class="lineno"> 61</span> <span class="comment"> * \note if return value is 0, the centroid is not changed, thus not valid.</span></div>
<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> <span class="comment"> * The last component of the vector is set to 1, this allows to transform the centroid vector with 4x4 matrices.</span></div>
<div class="line"><a name="l00063"></a><span class="lineno"> 63</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00064"></a><span class="lineno"> 64</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00066"></a><span class="lineno"> 66</span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (ConstCloudIterator<PointT> &cloud_iterator,</div>
<div class="line"><a name="l00067"></a><span class="lineno"> 67</span>  Eigen::Matrix<Scalar, 4, 1> &centroid);</div>
<div class="line"><a name="l00068"></a><span class="lineno"> 68</span>  </div>
<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00070"></a><span class="lineno"><a class="line" href="namespacepcl.html#ac050f06179c72e8bc2665faf7f42a0aa"> 70</a></span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<a class="code" href="classpcl_1_1_const_cloud_iterator.html">ConstCloudIterator<PointT></a> &cloud_iterator,</div>
<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  Eigen::Vector4f &centroid)</div>
<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  {</div>
<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  <span class="keywordflow">return</span> (compute3DCentroid <PointT, float> (cloud_iterator, centroid));</div>
<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  }</div>
<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  </div>
<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00077"></a><span class="lineno"><a class="line" href="namespacepcl.html#afda9ffdc3a6bb85098aa16e61d668682"> 77</a></span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<a class="code" href="classpcl_1_1_const_cloud_iterator.html">ConstCloudIterator<PointT></a> &cloud_iterator,</div>
<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  Eigen::Vector4d &centroid)</div>
<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  {</div>
<div class="line"><a name="l00080"></a><span class="lineno"> 80</span>  <span class="keywordflow">return</span> (compute3DCentroid <PointT, double> (cloud_iterator, centroid));</div>
<div class="line"><a name="l00081"></a><span class="lineno"> 81</span>  }</div>
<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="comment"></span> </div>
<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> <span class="comment"> /** \brief Compute the 3D (X-Y-Z) centroid of a set of points and return it as a 3D vector.</span></div>
<div class="line"><a name="l00084"></a><span class="lineno"> 84</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00085"></a><span class="lineno"> 85</span> <span class="comment"> * \param[out] centroid the output centroid</span></div>
<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> <span class="comment"> * \return number of valid points used to determine the centroid. In case of dense point clouds, this is the same as the size of input cloud.</span></div>
<div class="line"><a name="l00087"></a><span class="lineno"> 87</span> <span class="comment"> * \note if return value is 0, the centroid is not changed, thus not valid.</span></div>
<div class="line"><a name="l00088"></a><span class="lineno"> 88</span> <span class="comment"> * The last component of the vector is set to 1, this allows to transform the centroid vector with 4x4 matrices.</span></div>
<div class="line"><a name="l00089"></a><span class="lineno"> 89</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00090"></a><span class="lineno"> 90</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  Eigen::Matrix<Scalar, 4, 1> &centroid);</div>
<div class="line"><a name="l00094"></a><span class="lineno"> 94</span>  </div>
<div class="line"><a name="l00095"></a><span class="lineno"> 95</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00096"></a><span class="lineno"><a class="line" href="namespacepcl.html#a23daec3829d2d4100a2f185372b3753a"> 96</a></span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00097"></a><span class="lineno"> 97</span>  Eigen::Vector4f &centroid)</div>
<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  {</div>
<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  <span class="keywordflow">return</span> (compute3DCentroid <PointT, float> (cloud, centroid));</div>
<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  }</div>
<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  </div>
<div class="line"><a name="l00102"></a><span class="lineno"> 102</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00103"></a><span class="lineno"><a class="line" href="namespacepcl.html#a81f00705f1116eb69a984286e1e1d2b9"> 103</a></span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  Eigen::Vector4d &centroid)</div>
<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  {</div>
<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  <span class="keywordflow">return</span> (compute3DCentroid <PointT, double> (cloud, centroid));</div>
<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  }</div>
<div class="line"><a name="l00108"></a><span class="lineno"> 108</span> <span class="comment"></span> </div>
<div class="line"><a name="l00109"></a><span class="lineno"> 109</span> <span class="comment"> /** \brief Compute the 3D (X-Y-Z) centroid of a set of points using their indices and</span></div>
<div class="line"><a name="l00110"></a><span class="lineno"> 110</span> <span class="comment"> * return it as a 3D vector.</span></div>
<div class="line"><a name="l00111"></a><span class="lineno"> 111</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00112"></a><span class="lineno"> 112</span> <span class="comment"> * \param[in] indices the point cloud indices that need to be used</span></div>
<div class="line"><a name="l00113"></a><span class="lineno"> 113</span> <span class="comment"> * \param[out] centroid the output centroid</span></div>
<div class="line"><a name="l00114"></a><span class="lineno"> 114</span> <span class="comment"> * \return number of valid points used to determine the centroid. In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span> <span class="comment"> * \note if return value is 0, the centroid is not changed, thus not valid.</span></div>
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="comment"> * The last component of the vector is set to 1, this allows to transform the centroid vector with 4x4 matrices.</span></div>
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span>  Eigen::Matrix<Scalar, 4, 1> &centroid);</div>
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span>  </div>
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00125"></a><span class="lineno"><a class="line" href="namespacepcl.html#a7910e9ffc3a073679a0b87e73223d493"> 125</a></span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span>  Eigen::Vector4f &centroid)</div>
<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  {</div>
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span>  <span class="keywordflow">return</span> (compute3DCentroid <PointT, float> (cloud, indices, centroid));</div>
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  }</div>
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span>  </div>
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00133"></a><span class="lineno"><a class="line" href="namespacepcl.html#aa83cfc8af6f93b041f24fe2f4c6fa19c"> 133</a></span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  Eigen::Vector4d &centroid)</div>
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  {</div>
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  <span class="keywordflow">return</span> (compute3DCentroid <PointT, double> (cloud, indices, centroid));</div>
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span>  }</div>
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span> <span class="comment"></span> </div>
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span> <span class="comment"> /** \brief Compute the 3D (X-Y-Z) centroid of a set of points using their indices and</span></div>
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span> <span class="comment"> * return it as a 3D vector.</span></div>
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span> <span class="comment"> * \param[in] indices the point cloud indices that need to be used</span></div>
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span> <span class="comment"> * \param[out] centroid the output centroid</span></div>
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span> <span class="comment"> * \return number of valid points used to determine the centroid. In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span> <span class="comment"> * \note if return value is 0, the centroid is not changed, thus not valid.</span></div>
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span> <span class="comment"> * The last component of the vector is set to 1, this allows to transform the centroid vector with 4x4 matrices.</span></div>
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  Eigen::Matrix<Scalar, 4, 1> &centroid);</div>
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  </div>
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00156"></a><span class="lineno"><a class="line" href="namespacepcl.html#af4605825a1d7113456c905716c518e73"> 156</a></span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00157"></a><span class="lineno"> 157</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  Eigen::Vector4f &centroid)</div>
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  {</div>
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  <span class="keywordflow">return</span> (compute3DCentroid <PointT, float> (cloud, indices, centroid));</div>
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  }</div>
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  </div>
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00164"></a><span class="lineno"><a class="line" href="namespacepcl.html#a202572bfcc54d5262fb2ab3a695d7682"> 164</a></span>  <a class="code" href="group__common.html#gaf5729fae15603888b49743b118025290">compute3DCentroid</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00165"></a><span class="lineno"> 165</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  Eigen::Vector4d &centroid)</div>
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  {</div>
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="keywordflow">return</span> (compute3DCentroid <PointT, double> (cloud, indices, centroid));</div>
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  }</div>
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span> <span class="comment"></span> </div>
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span> <span class="comment"> /** \brief Compute the 3x3 covariance matrix of a given set of points.</span></div>
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span> <span class="comment"> * The result is returned as a Eigen::Matrix3f.</span></div>
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span> <span class="comment"> * Note: the covariance matrix is not normalized with the number of</span></div>
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="comment"> * points. For a normalized covariance, please use</span></div>
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span> <span class="comment"> * computeCovarianceMatrixNormalized.</span></div>
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span> <span class="comment"> * \param[in] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input cloud.</span></div>
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span> <span class="comment"> * \note if return value is 0, the covariance matrix is not changed, thus not valid.</span></div>
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  </div>
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00190"></a><span class="lineno"><a class="line" href="namespacepcl.html#a9a519f0128baede6be874e0947ad8147"> 190</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  {</div>
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, float> (cloud, centroid, covariance_matrix));</div>
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span>  }</div>
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  </div>
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00198"></a><span class="lineno"><a class="line" href="namespacepcl.html#a8b4e482f26037bee30f64693f33fa98e"> 198</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span>  {</div>
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, double> (cloud, centroid, covariance_matrix));</div>
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  }</div>
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span> <span class="comment"></span> </div>
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span> <span class="comment"> /** \brief Compute normalized the 3x3 covariance matrix of a given set of points.</span></div>
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span> <span class="comment"> * The result is returned as a Eigen::Matrix3f.</span></div>
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span> <span class="comment"> * Normalized means that every entry has been divided by the number of points in the point cloud.</span></div>
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, use computeCovarianceMatrix</span></div>
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span> <span class="comment"> * and scale the covariance matrix with 1 / (n-1), where n is the number of points used to calculate</span></div>
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span> <span class="comment"> * the covariance matrix and is returned by the computeCovarianceMatrix function.</span></div>
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span> <span class="comment"> * \param[in] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input cloud.</span></div>
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  </div>
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00224"></a><span class="lineno"><a class="line" href="namespacepcl.html#a7c34bc132bc8d638839f1ca4e8ddea0f"> 224</a></span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span>  {</div>
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span>  <span class="keywordflow">return</span> (computeCovarianceMatrixNormalized<PointT, float> (cloud, centroid, covariance_matrix));</div>
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span>  }</div>
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span>  </div>
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00232"></a><span class="lineno"><a class="line" href="namespacepcl.html#a5cf7877e22ed85622d8eea00880f7d35"> 232</a></span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span>  {</div>
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keywordflow">return</span> (computeCovarianceMatrixNormalized<PointT, double> (cloud, centroid, covariance_matrix));</div>
<div class="line"><a name="l00237"></a><span class="lineno"> 237</span>  }</div>
<div class="line"><a name="l00238"></a><span class="lineno"> 238</span> <span class="comment"></span> </div>
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span> <span class="comment"> /** \brief Compute the 3x3 covariance matrix of a given set of points using their indices.</span></div>
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span> <span class="comment"> * The result is returned as a Eigen::Matrix3f.</span></div>
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span> <span class="comment"> * Note: the covariance matrix is not normalized with the number of</span></div>
<div class="line"><a name="l00242"></a><span class="lineno"> 242</span> <span class="comment"> * points. For a normalized covariance, please use</span></div>
<div class="line"><a name="l00243"></a><span class="lineno"> 243</span> <span class="comment"> * computeCovarianceMatrixNormalized.</span></div>
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span> <span class="comment"> * \param[in] indices the point cloud indices that need to be used</span></div>
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="comment"> * \param[in] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span>  </div>
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00259"></a><span class="lineno"><a class="line" href="namespacepcl.html#a4c1e69343ca8a48a910292d60a5a98ca"> 259</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00260"></a><span class="lineno"> 260</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00261"></a><span class="lineno"> 261</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span>  {</div>
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, float> (cloud, indices, centroid, covariance_matrix));</div>
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span>  }</div>
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  </div>
<div class="line"><a name="l00267"></a><span class="lineno"> 267</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00268"></a><span class="lineno"><a class="line" href="namespacepcl.html#ae0cbcfc83901cd5e6508a3e57323ee44"> 268</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  {</div>
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, double> (cloud, indices, centroid, covariance_matrix));</div>
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  }</div>
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span> <span class="comment"></span> </div>
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span> <span class="comment"> /** \brief Compute the 3x3 covariance matrix of a given set of points using their indices.</span></div>
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span> <span class="comment"> * The result is returned as a Eigen::Matrix3f.</span></div>
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span> <span class="comment"> * Note: the covariance matrix is not normalized with the number of</span></div>
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span> <span class="comment"> * points. For a normalized covariance, please use</span></div>
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span> <span class="comment"> * computeCovarianceMatrixNormalized.</span></div>
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span> <span class="comment"> * \param[in] indices the point cloud indices that need to be used</span></div>
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span> <span class="comment"> * \param[in] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  </div>
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00296"></a><span class="lineno"><a class="line" href="namespacepcl.html#a327ececf41f1808237b5d7ef6f96494e"> 296</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  {</div>
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, float> (cloud, indices, centroid, covariance_matrix));</div>
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  }</div>
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  </div>
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00305"></a><span class="lineno"><a class="line" href="namespacepcl.html#a74070eb55600644b3f8de2d4d8d08bd2"> 305</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span>  {</div>
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, double> (cloud, indices, centroid, covariance_matrix));</div>
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  }</div>
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span> <span class="comment"></span> </div>
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span> <span class="comment"> /** \brief Compute the normalized 3x3 covariance matrix of a given set of points using</span></div>
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span> <span class="comment"> * their indices.</span></div>
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span> <span class="comment"> * The result is returned as a Eigen::Matrix3f.</span></div>
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span> <span class="comment"> * Normalized means that every entry has been divided by the number of entries in indices.</span></div>
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, use computeCovarianceMatrix</span></div>
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span> <span class="comment"> * and scale the covariance matrix with 1 / (n-1), where n is the number of points used to calculate</span></div>
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span> <span class="comment"> * the covariance matrix and is returned by the computeCovarianceMatrix function.</span></div>
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span> <span class="comment"> * \param[in] indices the point cloud indices that need to be used</span></div>
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span> <span class="comment"> * \param[in] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  </div>
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00335"></a><span class="lineno"><a class="line" href="namespacepcl.html#ae7afbcb20c186f0d3ee47b0f387ca54f"> 335</a></span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  {</div>
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span>  <span class="keywordflow">return</span> (computeCovarianceMatrixNormalized<PointT, float> (cloud, indices, centroid, covariance_matrix));</div>
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  }</div>
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  </div>
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00344"></a><span class="lineno"><a class="line" href="namespacepcl.html#ada0bf09f6b75ddb89ee99272606fa8bc"> 344</a></span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span>  {</div>
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordflow">return</span> (computeCovarianceMatrixNormalized<PointT, double> (cloud, indices, centroid, covariance_matrix));</div>
<div class="line"><a name="l00350"></a><span class="lineno"> 350</span>  }</div>
<div class="line"><a name="l00351"></a><span class="lineno"> 351</span> <span class="comment"></span> </div>
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span> <span class="comment"> /** \brief Compute the normalized 3x3 covariance matrix of a given set of points using</span></div>
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span> <span class="comment"> * their indices. The result is returned as a Eigen::Matrix3f.</span></div>
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span> <span class="comment"> * Normalized means that every entry has been divided by the number of entries in indices.</span></div>
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, use computeCovarianceMatrix</span></div>
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span> <span class="comment"> * and scale the covariance matrix with 1 / (n-1), where n is the number of points used to calculate</span></div>
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span> <span class="comment"> * the covariance matrix and is returned by the computeCovarianceMatrix function.</span></div>
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span> <span class="comment"> * \param[in] indices the point cloud indices that need to be used</span></div>
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span> <span class="comment"> * \param[in] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  </div>
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00373"></a><span class="lineno"><a class="line" href="namespacepcl.html#a8883fe1fb7c5c9de850f6520b68509f8"> 373</a></span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  {</div>
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  <span class="keywordflow">return</span> (computeCovarianceMatrixNormalized<PointT, float> (cloud, indices, centroid, covariance_matrix));</div>
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  }</div>
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  </div>
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00382"></a><span class="lineno"><a class="line" href="namespacepcl.html#a5fe0230defb5a7854e0234234c21506b"> 382</a></span>  <a class="code" href="group__common.html#gab5ea605f439a80daf6348547379bad8e">computeCovarianceMatrixNormalized</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  {</div>
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">return</span> (computeCovarianceMatrixNormalized<PointT, double> (cloud, indices, centroid, covariance_matrix));</div>
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  }</div>
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span> <span class="comment"></span> </div>
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span> <span class="comment"> /** \brief Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.</span></div>
<div class="line"><a name="l00391"></a><span class="lineno"> 391</span> <span class="comment"> * Normalized means that every entry has been divided by the number of valid entries in the point cloud.</span></div>
<div class="line"><a name="l00392"></a><span class="lineno"> 392</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, scale the covariance matrix</span></div>
<div class="line"><a name="l00393"></a><span class="lineno"> 393</span> <span class="comment"> * with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.</span></div>
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span> <span class="comment"> * \note This method is theoretically exact. However using float for internal calculations reduces the accuracy but increases the efficiency.</span></div>
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span> <span class="comment"> * \param[out] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input cloud.</span></div>
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix,</div>
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  Eigen::Matrix<Scalar, 4, 1> &centroid);</div>
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  </div>
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00408"></a><span class="lineno"><a class="line" href="namespacepcl.html#a8cc2ea3fcf34548958ee0d7e691fd150"> 408</a></span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  Eigen::Matrix3f &covariance_matrix,</div>
<div class="line"><a name="l00410"></a><span class="lineno"> 410</span>  Eigen::Vector4f &centroid)</div>
<div class="line"><a name="l00411"></a><span class="lineno"> 411</span>  {</div>
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span>  <span class="keywordflow">return</span> (computeMeanAndCovarianceMatrix<PointT, float> (cloud, covariance_matrix, centroid));</div>
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span>  }</div>
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span>  </div>
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00416"></a><span class="lineno"><a class="line" href="namespacepcl.html#a21277bc4c42f68a98091745b9fd8232f"> 416</a></span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span>  Eigen::Matrix3d &covariance_matrix,</div>
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span>  Eigen::Vector4d &centroid)</div>
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span>  {</div>
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span>  <span class="keywordflow">return</span> (computeMeanAndCovarianceMatrix<PointT, double> (cloud, covariance_matrix, centroid));</div>
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span>  }</div>
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span> <span class="comment"></span> </div>
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span> <span class="comment"> /** \brief Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.</span></div>
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span> <span class="comment"> * Normalized means that every entry has been divided by the number of entries in indices.</span></div>
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, scale the covariance matrix</span></div>
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span> <span class="comment"> * with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.</span></div>
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span> <span class="comment"> * \note This method is theoretically exact. However using float for internal calculations reduces the accuracy but increases the efficiency.</span></div>
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span> <span class="comment"> * \param[in] indices subset of points given by their indices</span></div>
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span> <span class="comment"> * \param[out] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00432"></a><span class="lineno"> 432</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00433"></a><span class="lineno"> 433</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix,</div>
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  Eigen::Matrix<Scalar, 4, 1> &centroid);</div>
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span>  </div>
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00443"></a><span class="lineno"><a class="line" href="namespacepcl.html#a764daf3dce844d19e671d65954b626bd"> 443</a></span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span>  Eigen::Matrix3f &covariance_matrix,</div>
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  Eigen::Vector4f &centroid)</div>
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  {</div>
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <span class="keywordflow">return</span> (computeMeanAndCovarianceMatrix<PointT, float> (cloud, indices, covariance_matrix, centroid));</div>
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  }</div>
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  </div>
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00452"></a><span class="lineno"><a class="line" href="namespacepcl.html#a1ba133631e4a1c60f26412cd917d25a2"> 452</a></span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  Eigen::Matrix3d &covariance_matrix,</div>
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  Eigen::Vector4d &centroid)</div>
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span>  {</div>
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keywordflow">return</span> (computeMeanAndCovarianceMatrix<PointT, double> (cloud, indices, covariance_matrix, centroid));</div>
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  }</div>
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span> <span class="comment"></span> </div>
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span> <span class="comment"> /** \brief Compute the normalized 3x3 covariance matrix and the centroid of a given set of points in a single loop.</span></div>
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span> <span class="comment"> * Normalized means that every entry has been divided by the number of entries in indices.</span></div>
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, scale the covariance matrix</span></div>
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span> <span class="comment"> * with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.</span></div>
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span> <span class="comment"> * \note This method is theoretically exact. However using float for internal calculations reduces the accuracy but increases the efficiency.</span></div>
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span> <span class="comment"> * \param[in] indices subset of points given by their indices</span></div>
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span> <span class="comment"> * \param[out] centroid the centroid of the set of points in the cloud</span></div>
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix,</div>
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span>  Eigen::Matrix<Scalar, 4, 1> &centroid);</div>
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  </div>
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00480"></a><span class="lineno"><a class="line" href="namespacepcl.html#ac84951a6b448e68f38b93db5d657c833"> 480</a></span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00481"></a><span class="lineno"> 481</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00482"></a><span class="lineno"> 482</span>  Eigen::Matrix3f &covariance_matrix,</div>
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  Eigen::Vector4f &centroid)</div>
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span>  {</div>
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="keywordflow">return</span> (computeMeanAndCovarianceMatrix<PointT, float> (cloud, indices, covariance_matrix, centroid));</div>
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  }</div>
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span>  </div>
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00489"></a><span class="lineno"><a class="line" href="namespacepcl.html#aeff94982be65cb242843ce845a9fa1be"> 489</a></span>  <a class="code" href="group__common.html#ga72dfb6e965df9752c88790e026a8ab5f">computeMeanAndCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span>  Eigen::Matrix3d &covariance_matrix,</div>
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span>  Eigen::Vector4d &centroid)</div>
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  {</div>
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  <span class="keywordflow">return</span> (computeMeanAndCovarianceMatrix<PointT, double> (cloud, indices, covariance_matrix, centroid));</div>
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span>  }</div>
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span> <span class="comment"></span> </div>
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span> <span class="comment"> /** \brief Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.</span></div>
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span> <span class="comment"> * Normalized means that every entry has been divided by the number of entries in the input point cloud.</span></div>
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, scale the covariance matrix</span></div>
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span> <span class="comment"> * with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.</span></div>
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span> <span class="comment"> * \note This method is theoretically exact. However using float for internal calculations reduces the accuracy but increases the efficiency.</span></div>
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00504"></a><span class="lineno"> 504</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00505"></a><span class="lineno"> 505</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input cloud.</span></div>
<div class="line"><a name="l00506"></a><span class="lineno"> 506</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span>  </div>
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00513"></a><span class="lineno"><a class="line" href="namespacepcl.html#a1792af32d68f02d0ae84aea7c25cf6d3"> 513</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  {</div>
<div class="line"><a name="l00516"></a><span class="lineno"> 516</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, float> (cloud, covariance_matrix));</div>
<div class="line"><a name="l00517"></a><span class="lineno"> 517</span>  }</div>
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  </div>
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00520"></a><span class="lineno"><a class="line" href="namespacepcl.html#a8cc2952e9da0204aed64bb967886240c"> 520</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  {</div>
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, double> (cloud, covariance_matrix));</div>
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  }</div>
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span> <span class="comment"></span> </div>
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span> <span class="comment"> /** \brief Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.</span></div>
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span> <span class="comment"> * Normalized means that every entry has been divided by the number of entries in indices.</span></div>
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, scale the covariance matrix</span></div>
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span> <span class="comment"> * with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.</span></div>
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span> <span class="comment"> * \note This method is theoretically exact. However using float for internal calculations reduces the accuracy but increases the efficiency.</span></div>
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span> <span class="comment"> * \param[in] indices subset of points given by their indices</span></div>
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00542"></a><span class="lineno"> 542</span>  </div>
<div class="line"><a name="l00543"></a><span class="lineno"> 543</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00544"></a><span class="lineno"><a class="line" href="namespacepcl.html#a2804d83d939167e5dfce426d4039ab3f"> 544</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  {</div>
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, float> (cloud, indices, covariance_matrix));</div>
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  }</div>
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span>  </div>
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00552"></a><span class="lineno"><a class="line" href="namespacepcl.html#af2c48ee806ee373875f1cdd8b9091236"> 552</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  {</div>
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, double> (cloud, indices, covariance_matrix));</div>
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  }</div>
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span> <span class="comment"></span> </div>
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span> <span class="comment"> /** \brief Compute the normalized 3x3 covariance matrix for a already demeaned point cloud.</span></div>
<div class="line"><a name="l00560"></a><span class="lineno"> 560</span> <span class="comment"> * Normalized means that every entry has been divided by the number of entries in indices.</span></div>
<div class="line"><a name="l00561"></a><span class="lineno"> 561</span> <span class="comment"> * For small number of points, or if you want explicitly the sample-variance, scale the covariance matrix</span></div>
<div class="line"><a name="l00562"></a><span class="lineno"> 562</span> <span class="comment"> * with n / (n-1), where n is the number of points used to calculate the covariance matrix and is returned by this function.</span></div>
<div class="line"><a name="l00563"></a><span class="lineno"> 563</span> <span class="comment"> * \note This method is theoretically exact. However using float for internal calculations reduces the accuracy but increases the efficiency.</span></div>
<div class="line"><a name="l00564"></a><span class="lineno"> 564</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00565"></a><span class="lineno"> 565</span> <span class="comment"> * \param[in] indices subset of points given by their indices</span></div>
<div class="line"><a name="l00566"></a><span class="lineno"> 566</span> <span class="comment"> * \param[out] covariance_matrix the resultant 3x3 covariance matrix</span></div>
<div class="line"><a name="l00567"></a><span class="lineno"> 567</span> <span class="comment"> * \return number of valid points used to determine the covariance matrix.</span></div>
<div class="line"><a name="l00568"></a><span class="lineno"> 568</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of input indices.</span></div>
<div class="line"><a name="l00569"></a><span class="lineno"> 569</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00570"></a><span class="lineno"> 570</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span>  Eigen::Matrix<Scalar, 3, 3> &covariance_matrix);</div>
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  </div>
<div class="line"><a name="l00576"></a><span class="lineno"> 576</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00577"></a><span class="lineno"><a class="line" href="namespacepcl.html#a63b7fbcd5a7bf264c08d5b7b534d34fe"> 577</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00579"></a><span class="lineno"> 579</span>  Eigen::Matrix3f &covariance_matrix)</div>
<div class="line"><a name="l00580"></a><span class="lineno"> 580</span>  {</div>
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, float> (cloud, indices, covariance_matrix));</div>
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span>  }</div>
<div class="line"><a name="l00583"></a><span class="lineno"> 583</span>  </div>
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00585"></a><span class="lineno"><a class="line" href="namespacepcl.html#ad570c977482c84dc1fd2ec82ff664bc5"> 585</a></span>  <a class="code" href="group__common.html#gac36b146ec26b1ceb7be43a9ecaa010c4">computeCovarianceMatrix</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud,</div>
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a> &indices,</div>
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  Eigen::Matrix3d &covariance_matrix)</div>
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  {</div>
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span>  <span class="keywordflow">return</span> (computeCovarianceMatrix<PointT, double> (cloud, indices, covariance_matrix));</div>
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span>  }</div>
<div class="line"><a name="l00591"></a><span class="lineno"> 591</span>  </div>
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span> <span class="comment"></span> </div>
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span> <span class="comment"> /** \brief Compute centroid, OBB (Oriented Bounding Box), PCA axes of a given set of points.</span></div>
<div class="line"><a name="l00594"></a><span class="lineno"> 594</span> <span class="comment"> * OBB is oriented like the three axes (major, middle and minor) with</span></div>
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span> <span class="comment"> * major_axis = obb_rotational_matrix.col(0)</span></div>
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span> <span class="comment"> * middle_axis = obb_rotational_matrix.col(1)</span></div>
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span> <span class="comment"> * minor_axis = obb_rotational_matrix.col(2)</span></div>
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span> <span class="comment"> * one way to visualize OBB when Scalar is float:</span></div>
<div class="line"><a name="l00599"></a><span class="lineno"> 599</span> <span class="comment"> * Eigen::Vector3f position(obb_position(0), obb_position(1), obb_position(2));</span></div>
<div class="line"><a name="l00600"></a><span class="lineno"> 600</span> <span class="comment"> * Eigen::Quaternionf quat(obb_rotational_matrix);</span></div>
<div class="line"><a name="l00601"></a><span class="lineno"> 601</span> <span class="comment"> * viewer->addCube(position, quat, obb_dimensions(0), obb_dimensions(1), obb_dimensions(2), .....);</span></div>
<div class="line"><a name="l00602"></a><span class="lineno"> 602</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00603"></a><span class="lineno"> 603</span> <span class="comment"> * \param[out] centroid the centroid (mean value of the XYZ coordinates) of the set of points in the cloud</span></div>
<div class="line"><a name="l00604"></a><span class="lineno"> 604</span> <span class="comment"> * \param[out] obb_center position of the center of the OBB (it is the same as centroid if the cloud is centrally symmetric)</span></div>
<div class="line"><a name="l00605"></a><span class="lineno"> 605</span> <span class="comment"> * \param[out] obb_dimensions (width, height and depth) of the OBB </span></div>
<div class="line"><a name="l00606"></a><span class="lineno"> 606</span> <span class="comment"> * \param[out] obb_rotational_matrix rotational matrix of the OBB </span></div>
<div class="line"><a name="l00607"></a><span class="lineno"> 607</span> <span class="comment"> * \return number of valid points used to determine the output.</span></div>
<div class="line"><a name="l00608"></a><span class="lineno"> 608</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of the input cloud.</span></div>
<div class="line"><a name="l00609"></a><span class="lineno"> 609</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00610"></a><span class="lineno"> 610</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <a class="code" href="group__common.html#ga0ef093d77f87e8a3acb288fe6b8fa397">computeCentroidAndOBB</a>(<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a>& cloud,</div>
<div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  Eigen::Matrix<Scalar, 3, 1>& centroid,</div>
<div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  Eigen::Matrix<Scalar, 3, 1>& obb_center,</div>
<div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  Eigen::Matrix<Scalar, 3, 1>& obb_dimensions,</div>
<div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  Eigen::Matrix<Scalar, 3, 3>& obb_rotational_matrix);</div>
<div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  </div>
<div class="line"><a name="l00618"></a><span class="lineno"> 618</span> <span class="comment"></span> </div>
<div class="line"><a name="l00619"></a><span class="lineno"> 619</span> <span class="comment"> /** \brief Compute centroid, OBB (Oriented Bounding Box), PCA axes of a given set of points.</span></div>
<div class="line"><a name="l00620"></a><span class="lineno"> 620</span> <span class="comment"> * OBB is oriented like the three axes (major, middle and minor) with</span></div>
<div class="line"><a name="l00621"></a><span class="lineno"> 621</span> <span class="comment"> * major_axis = obb_rotational_matrix.col(0)</span></div>
<div class="line"><a name="l00622"></a><span class="lineno"> 622</span> <span class="comment"> * middle_axis = obb_rotational_matrix.col(1)</span></div>
<div class="line"><a name="l00623"></a><span class="lineno"> 623</span> <span class="comment"> * minor_axis = obb_rotational_matrix.col(2)</span></div>
<div class="line"><a name="l00624"></a><span class="lineno"> 624</span> <span class="comment"> * one way to visualize OBB when Scalar is float:</span></div>
<div class="line"><a name="l00625"></a><span class="lineno"> 625</span> <span class="comment"> * Eigen::Vector3f position(obb_position(0), obb_position(1), obb_position(2));</span></div>
<div class="line"><a name="l00626"></a><span class="lineno"> 626</span> <span class="comment"> * Eigen::Quaternionf quat(obb_rotational_matrix);</span></div>
<div class="line"><a name="l00627"></a><span class="lineno"> 627</span> <span class="comment"> * viewer->addCube(position, quat, obb_dimensions(0), obb_dimensions(1), obb_dimensions(2), .....);</span></div>
<div class="line"><a name="l00628"></a><span class="lineno"> 628</span> <span class="comment"> * \param[in] cloud the input point cloud</span></div>
<div class="line"><a name="l00629"></a><span class="lineno"> 629</span> <span class="comment"> * \param[in] indices subset of points given by their indices </span></div>
<div class="line"><a name="l00630"></a><span class="lineno"> 630</span> <span class="comment"> * \param[out] centroid the centroid (mean value of the XYZ coordinates) of the set of points in the cloud</span></div>
<div class="line"><a name="l00631"></a><span class="lineno"> 631</span> <span class="comment"> * \param[out] obb_center position of the center of the OBB (it is the same as centroid if the cloud is centrally symmetric)</span></div>
<div class="line"><a name="l00632"></a><span class="lineno"> 632</span> <span class="comment"> * \param[out] obb_dimensions (width, height and depth) of the OBB </span></div>
<div class="line"><a name="l00633"></a><span class="lineno"> 633</span> <span class="comment"> * \param[out] obb_rotational_matrix rotational matrix of the OBB </span></div>
<div class="line"><a name="l00634"></a><span class="lineno"> 634</span> <span class="comment"> * \return number of valid points used to determine the output.</span></div>
<div class="line"><a name="l00635"></a><span class="lineno"> 635</span> <span class="comment"> * In case of dense point clouds, this is the same as the size of the input cloud.</span></div>
<div class="line"><a name="l00636"></a><span class="lineno"> 636</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00637"></a><span class="lineno"> 637</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keyword">inline</span> <span class="keywordtype">unsigned</span> <span class="keywordtype">int</span></div>
<div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  <a class="code" href="group__common.html#ga0ef093d77f87e8a3acb288fe6b8fa397">computeCentroidAndOBB</a>(<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a>& cloud,</div>
<div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  Eigen::Matrix<Scalar, 3, 1>& centroid,</div>
<div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  Eigen::Matrix<Scalar, 3, 1>& obb_center,</div>
<div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  Eigen::Matrix<Scalar, 3, 1>& obb_dimensions,</div>
<div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  Eigen::Matrix<Scalar, 3, 3>& obb_rotational_matrix);</div>
<div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  </div>
<div class="line"><a name="l00646"></a><span class="lineno"> 646</span> <span class="comment"></span> </div>
<div class="line"><a name="l00647"></a><span class="lineno"> 647</span> <span class="comment"> /** \brief Subtract a centroid from a point cloud and return the de-meaned representation</span></div>
<div class="line"><a name="l00648"></a><span class="lineno"> 648</span> <span class="comment"> * \param[in] cloud_iterator an iterator over the input point cloud</span></div>
<div class="line"><a name="l00649"></a><span class="lineno"> 649</span> <span class="comment"> * \param[in] centroid the centroid of the point cloud</span></div>
<div class="line"><a name="l00650"></a><span class="lineno"> 650</span> <span class="comment"> * \param[out] cloud_out the resultant output point cloud</span></div>
<div class="line"><a name="l00651"></a><span class="lineno"> 651</span> <span class="comment"> * \param[in] npts the number of samples guaranteed to be left in the input cloud, accessible by the iterator. If not given, it will be calculated.</span></div>
<div class="line"><a name="l00652"></a><span class="lineno"> 652</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00653"></a><span class="lineno"> 653</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00654"></a><span class="lineno"> 654</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00655"></a><span class="lineno"> 655</span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (ConstCloudIterator<PointT> &cloud_iterator,</div>
<div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out,</div>
<div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  <span class="keywordtype">int</span> npts = 0);</div>
<div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  </div>
<div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00661"></a><span class="lineno"><a class="line" href="namespacepcl.html#a0212a746948007708bcfaa4117ea7461"> 661</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<a class="code" href="classpcl_1_1_const_cloud_iterator.html">ConstCloudIterator<PointT></a> &cloud_iterator,</div>
<div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out,</div>
<div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  <span class="keywordtype">int</span> npts = 0)</div>
<div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  {</div>
<div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, float> (cloud_iterator, centroid, cloud_out, npts));</div>
<div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  }</div>
<div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  </div>
<div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00670"></a><span class="lineno"><a class="line" href="namespacepcl.html#a71766012ea8618588baa1dc073dac1b4"> 670</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<a class="code" href="classpcl_1_1_const_cloud_iterator.html">ConstCloudIterator<PointT></a> &cloud_iterator,</div>
<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00672"></a><span class="lineno"> 672</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out,</div>
<div class="line"><a name="l00673"></a><span class="lineno"> 673</span>  <span class="keywordtype">int</span> npts = 0)</div>
<div class="line"><a name="l00674"></a><span class="lineno"> 674</span>  {</div>
<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, double> (cloud_iterator, centroid, cloud_out, npts));</div>
<div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  }</div>
<div class="line"><a name="l00677"></a><span class="lineno"> 677</span> <span class="comment"></span> </div>
<div class="line"><a name="l00678"></a><span class="lineno"> 678</span> <span class="comment"> /** \brief Subtract a centroid from a point cloud and return the de-meaned representation</span></div>
<div class="line"><a name="l00679"></a><span class="lineno"> 679</span> <span class="comment"> * \param[in] cloud_in the input point cloud</span></div>
<div class="line"><a name="l00680"></a><span class="lineno"> 680</span> <span class="comment"> * \param[in] centroid the centroid of the point cloud</span></div>
<div class="line"><a name="l00681"></a><span class="lineno"> 681</span> <span class="comment"> * \param[out] cloud_out the resultant output point cloud</span></div>
<div class="line"><a name="l00682"></a><span class="lineno"> 682</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00683"></a><span class="lineno"> 683</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00684"></a><span class="lineno"> 684</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00685"></a><span class="lineno"> 685</span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00686"></a><span class="lineno"> 686</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out);</div>
<div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  </div>
<div class="line"><a name="l00689"></a><span class="lineno"> 689</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00690"></a><span class="lineno"><a class="line" href="namespacepcl.html#ae1ca17f3decd37c512d958afa4d88ce0"> 690</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<a class="code" href="classpcl_1_1_const_cloud_iterator.html">ConstCloudIterator<PointT></a> &cloud_iterator,</div>
<div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00692"></a><span class="lineno"> 692</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out)</div>
<div class="line"><a name="l00693"></a><span class="lineno"> 693</span>  {</div>
<div class="line"><a name="l00694"></a><span class="lineno"> 694</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, float> (cloud_iterator, centroid, cloud_out));</div>
<div class="line"><a name="l00695"></a><span class="lineno"> 695</span>  }</div>
<div class="line"><a name="l00696"></a><span class="lineno"> 696</span>  </div>
<div class="line"><a name="l00697"></a><span class="lineno"> 697</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00698"></a><span class="lineno"><a class="line" href="namespacepcl.html#a6afc80fd70f4436ccce44de9241a1ba3"> 698</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<a class="code" href="classpcl_1_1_const_cloud_iterator.html">ConstCloudIterator<PointT></a> &cloud_iterator,</div>
<div class="line"><a name="l00699"></a><span class="lineno"> 699</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out)</div>
<div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  {</div>
<div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, double> (cloud_iterator, centroid, cloud_out));</div>
<div class="line"><a name="l00703"></a><span class="lineno"> 703</span>  }</div>
<div class="line"><a name="l00704"></a><span class="lineno"> 704</span> <span class="comment"></span> </div>
<div class="line"><a name="l00705"></a><span class="lineno"> 705</span> <span class="comment"> /** \brief Subtract a centroid from a point cloud and return the de-meaned representation</span></div>
<div class="line"><a name="l00706"></a><span class="lineno"> 706</span> <span class="comment"> * \param[in] cloud_in the input point cloud</span></div>
<div class="line"><a name="l00707"></a><span class="lineno"> 707</span> <span class="comment"> * \param[in] indices the set of point indices to use from the input point cloud</span></div>
<div class="line"><a name="l00708"></a><span class="lineno"> 708</span> <span class="comment"> * \param[out] centroid the centroid of the point cloud</span></div>
<div class="line"><a name="l00709"></a><span class="lineno"> 709</span> <span class="comment"> * \param cloud_out the resultant output point cloud</span></div>
<div class="line"><a name="l00710"></a><span class="lineno"> 710</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00711"></a><span class="lineno"> 711</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00712"></a><span class="lineno"> 712</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00713"></a><span class="lineno"> 713</span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00714"></a><span class="lineno"> 714</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out);</div>
<div class="line"><a name="l00717"></a><span class="lineno"> 717</span>  </div>
<div class="line"><a name="l00718"></a><span class="lineno"> 718</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00719"></a><span class="lineno"><a class="line" href="namespacepcl.html#a47aca32be73611921c4a0ece73818465"> 719</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00720"></a><span class="lineno"> 720</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out)</div>
<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  {</div>
<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, float> (cloud_in, indices, centroid, cloud_out));</div>
<div class="line"><a name="l00725"></a><span class="lineno"> 725</span>  }</div>
<div class="line"><a name="l00726"></a><span class="lineno"> 726</span>  </div>
<div class="line"><a name="l00727"></a><span class="lineno"> 727</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00728"></a><span class="lineno"><a class="line" href="namespacepcl.html#ade3c09b0bae4898312b3f1720cf35d77"> 728</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out)</div>
<div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  {</div>
<div class="line"><a name="l00733"></a><span class="lineno"> 733</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, double> (cloud_in, indices, centroid, cloud_out));</div>
<div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  }</div>
<div class="line"><a name="l00735"></a><span class="lineno"> 735</span> <span class="comment"></span> </div>
<div class="line"><a name="l00736"></a><span class="lineno"> 736</span> <span class="comment"> /** \brief Subtract a centroid from a point cloud and return the de-meaned representation</span></div>
<div class="line"><a name="l00737"></a><span class="lineno"> 737</span> <span class="comment"> * \param[in] cloud_in the input point cloud</span></div>
<div class="line"><a name="l00738"></a><span class="lineno"> 738</span> <span class="comment"> * \param[in] indices the set of point indices to use from the input point cloud</span></div>
<div class="line"><a name="l00739"></a><span class="lineno"> 739</span> <span class="comment"> * \param[out] centroid the centroid of the point cloud</span></div>
<div class="line"><a name="l00740"></a><span class="lineno"> 740</span> <span class="comment"> * \param cloud_out the resultant output point cloud</span></div>
<div class="line"><a name="l00741"></a><span class="lineno"> 741</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00742"></a><span class="lineno"> 742</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00744"></a><span class="lineno"> 744</span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a>& indices,</div>
<div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00747"></a><span class="lineno"> 747</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out);</div>
<div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  </div>
<div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00750"></a><span class="lineno"><a class="line" href="namespacepcl.html#a1b9d4b8b8ac294c8273318b7af44b477"> 750</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a>& indices,</div>
<div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out)</div>
<div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  {</div>
<div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, float> (cloud_in, indices, centroid, cloud_out));</div>
<div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  }</div>
<div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  </div>
<div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00759"></a><span class="lineno"><a class="line" href="namespacepcl.html#a989ce2a2f9a6f14cbfefee1a3eaa40e6"> 759</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00760"></a><span class="lineno"> 760</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a>& indices,</div>
<div class="line"><a name="l00761"></a><span class="lineno"> 761</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_out)</div>
<div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  {</div>
<div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, double> (cloud_in, indices, centroid, cloud_out));</div>
<div class="line"><a name="l00765"></a><span class="lineno"> 765</span>  }</div>
<div class="line"><a name="l00766"></a><span class="lineno"> 766</span> <span class="comment"></span> </div>
<div class="line"><a name="l00767"></a><span class="lineno"> 767</span> <span class="comment"> /** \brief Subtract a centroid from a point cloud and return the de-meaned</span></div>
<div class="line"><a name="l00768"></a><span class="lineno"> 768</span> <span class="comment"> * representation as an Eigen matrix</span></div>
<div class="line"><a name="l00769"></a><span class="lineno"> 769</span> <span class="comment"> * \param[in] cloud_iterator an iterator over the input point cloud</span></div>
<div class="line"><a name="l00770"></a><span class="lineno"> 770</span> <span class="comment"> * \param[in] centroid the centroid of the point cloud</span></div>
<div class="line"><a name="l00771"></a><span class="lineno"> 771</span> <span class="comment"> * \param[out] cloud_out the resultant output XYZ0 dimensions of \a cloud_in as</span></div>
<div class="line"><a name="l00772"></a><span class="lineno"> 772</span> <span class="comment"> * an Eigen matrix (4 rows, N pts columns)</span></div>
<div class="line"><a name="l00773"></a><span class="lineno"> 773</span> <span class="comment"> * \param[in] npts the number of samples guaranteed to be left in the input cloud, accessible by the iterator. If not given, it will be calculated.</span></div>
<div class="line"><a name="l00774"></a><span class="lineno"> 774</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00775"></a><span class="lineno"> 775</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (ConstCloudIterator<PointT> &cloud_iterator,</div>
<div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> &cloud_out,</div>
<div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  <span class="keywordtype">int</span> npts = 0);</div>
<div class="line"><a name="l00781"></a><span class="lineno"> 781</span>  </div>
<div class="line"><a name="l00782"></a><span class="lineno"> 782</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00783"></a><span class="lineno"><a class="line" href="namespacepcl.html#ae5a74008d2df6abde28a843a243ef011"> 783</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<a class="code" href="classpcl_1_1_const_cloud_iterator.html">ConstCloudIterator<PointT></a> &cloud_iterator,</div>
<div class="line"><a name="l00784"></a><span class="lineno"> 784</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00785"></a><span class="lineno"> 785</span>  Eigen::MatrixXf &cloud_out,</div>
<div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  <span class="keywordtype">int</span> npts = 0)</div>
<div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  {</div>
<div class="line"><a name="l00788"></a><span class="lineno"> 788</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, float> (cloud_iterator, centroid, cloud_out, npts));</div>
<div class="line"><a name="l00789"></a><span class="lineno"> 789</span>  }</div>
<div class="line"><a name="l00790"></a><span class="lineno"> 790</span>  </div>
<div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00792"></a><span class="lineno"><a class="line" href="namespacepcl.html#a3a54767789c47edda970ae0cc04aee33"> 792</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<a class="code" href="classpcl_1_1_const_cloud_iterator.html">ConstCloudIterator<PointT></a> &cloud_iterator,</div>
<div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  Eigen::MatrixXd &cloud_out,</div>
<div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <span class="keywordtype">int</span> npts = 0)</div>
<div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  {</div>
<div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, double> (cloud_iterator, centroid, cloud_out, npts));</div>
<div class="line"><a name="l00798"></a><span class="lineno"> 798</span>  }</div>
<div class="line"><a name="l00799"></a><span class="lineno"> 799</span> <span class="comment"></span> </div>
<div class="line"><a name="l00800"></a><span class="lineno"> 800</span> <span class="comment"> /** \brief Subtract a centroid from a point cloud and return the de-meaned</span></div>
<div class="line"><a name="l00801"></a><span class="lineno"> 801</span> <span class="comment"> * representation as an Eigen matrix</span></div>
<div class="line"><a name="l00802"></a><span class="lineno"> 802</span> <span class="comment"> * \param[in] cloud_in the input point cloud</span></div>
<div class="line"><a name="l00803"></a><span class="lineno"> 803</span> <span class="comment"> * \param[in] centroid the centroid of the point cloud</span></div>
<div class="line"><a name="l00804"></a><span class="lineno"> 804</span> <span class="comment"> * \param[out] cloud_out the resultant output XYZ0 dimensions of \a cloud_in as</span></div>
<div class="line"><a name="l00805"></a><span class="lineno"> 805</span> <span class="comment"> * an Eigen matrix (4 rows, N pts columns)</span></div>
<div class="line"><a name="l00806"></a><span class="lineno"> 806</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00807"></a><span class="lineno"> 807</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00808"></a><span class="lineno"> 808</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00809"></a><span class="lineno"> 809</span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00810"></a><span class="lineno"> 810</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> &cloud_out);</div>
<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  </div>
<div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00814"></a><span class="lineno"><a class="line" href="namespacepcl.html#a8dfb2a1c7a8437bac36540227bc55888"> 814</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00815"></a><span class="lineno"> 815</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  Eigen::MatrixXf &cloud_out)</div>
<div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  {</div>
<div class="line"><a name="l00818"></a><span class="lineno"> 818</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, float> (cloud_in, centroid, cloud_out));</div>
<div class="line"><a name="l00819"></a><span class="lineno"> 819</span>  }</div>
<div class="line"><a name="l00820"></a><span class="lineno"> 820</span>  </div>
<div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00822"></a><span class="lineno"><a class="line" href="namespacepcl.html#a9820d1ad515c00d37ef4c7594b27d1ab"> 822</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00823"></a><span class="lineno"> 823</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00824"></a><span class="lineno"> 824</span>  Eigen::MatrixXd &cloud_out)</div>
<div class="line"><a name="l00825"></a><span class="lineno"> 825</span>  {</div>
<div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, double> (cloud_in, centroid, cloud_out));</div>
<div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  }</div>
<div class="line"><a name="l00828"></a><span class="lineno"> 828</span> <span class="comment"></span> </div>
<div class="line"><a name="l00829"></a><span class="lineno"> 829</span> <span class="comment"> /** \brief Subtract a centroid from a point cloud and return the de-meaned</span></div>
<div class="line"><a name="l00830"></a><span class="lineno"> 830</span> <span class="comment"> * representation as an Eigen matrix</span></div>
<div class="line"><a name="l00831"></a><span class="lineno"> 831</span> <span class="comment"> * \param[in] cloud_in the input point cloud</span></div>
<div class="line"><a name="l00832"></a><span class="lineno"> 832</span> <span class="comment"> * \param[in] indices the set of point indices to use from the input point cloud</span></div>
<div class="line"><a name="l00833"></a><span class="lineno"> 833</span> <span class="comment"> * \param[in] centroid the centroid of the point cloud</span></div>
<div class="line"><a name="l00834"></a><span class="lineno"> 834</span> <span class="comment"> * \param[out] cloud_out the resultant output XYZ0 dimensions of \a cloud_in as</span></div>
<div class="line"><a name="l00835"></a><span class="lineno"> 835</span> <span class="comment"> * an Eigen matrix (4 rows, N pts columns)</span></div>
<div class="line"><a name="l00836"></a><span class="lineno"> 836</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00837"></a><span class="lineno"> 837</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00838"></a><span class="lineno"> 838</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00839"></a><span class="lineno"> 839</span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00840"></a><span class="lineno"> 840</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00841"></a><span class="lineno"> 841</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00842"></a><span class="lineno"> 842</span>  Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> &cloud_out);</div>
<div class="line"><a name="l00843"></a><span class="lineno"> 843</span>  </div>
<div class="line"><a name="l00844"></a><span class="lineno"> 844</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00845"></a><span class="lineno"><a class="line" href="namespacepcl.html#ad4cff987767d4fb99e5ddb8fbe6c72e4"> 845</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  Eigen::MatrixXf &cloud_out)</div>
<div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  {</div>
<div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, float> (cloud_in, indices, centroid, cloud_out));</div>
<div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  }</div>
<div class="line"><a name="l00852"></a><span class="lineno"> 852</span>  </div>
<div class="line"><a name="l00853"></a><span class="lineno"> 853</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00854"></a><span class="lineno"><a class="line" href="namespacepcl.html#ae10afd64292643e9d04ffcf12b876069"> 854</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  <span class="keyword">const</span> <a class="code" href="namespacepcl.html#a8bfe09b8680e7129dd0fd6177c1a2ce6">Indices</a> &indices,</div>
<div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  Eigen::MatrixXd &cloud_out)</div>
<div class="line"><a name="l00858"></a><span class="lineno"> 858</span>  {</div>
<div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, double> (cloud_in, indices, centroid, cloud_out));</div>
<div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  }</div>
<div class="line"><a name="l00861"></a><span class="lineno"> 861</span> <span class="comment"></span> </div>
<div class="line"><a name="l00862"></a><span class="lineno"> 862</span> <span class="comment"> /** \brief Subtract a centroid from a point cloud and return the de-meaned</span></div>
<div class="line"><a name="l00863"></a><span class="lineno"> 863</span> <span class="comment"> * representation as an Eigen matrix</span></div>
<div class="line"><a name="l00864"></a><span class="lineno"> 864</span> <span class="comment"> * \param[in] cloud_in the input point cloud</span></div>
<div class="line"><a name="l00865"></a><span class="lineno"> 865</span> <span class="comment"> * \param[in] indices the set of point indices to use from the input point cloud</span></div>
<div class="line"><a name="l00866"></a><span class="lineno"> 866</span> <span class="comment"> * \param[in] centroid the centroid of the point cloud</span></div>
<div class="line"><a name="l00867"></a><span class="lineno"> 867</span> <span class="comment"> * \param[out] cloud_out the resultant output XYZ0 dimensions of \a cloud_in as</span></div>
<div class="line"><a name="l00868"></a><span class="lineno"> 868</span> <span class="comment"> * an Eigen matrix (4 rows, N pts columns)</span></div>
<div class="line"><a name="l00869"></a><span class="lineno"> 869</span> <span class="comment"> * \ingroup common</span></div>
<div class="line"><a name="l00870"></a><span class="lineno"> 870</span> <span class="comment"> */</span></div>
<div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00872"></a><span class="lineno"> 872</span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a>& indices,</div>
<div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  <span class="keyword">const</span> Eigen::Matrix<Scalar, 4, 1> &centroid,</div>
<div class="line"><a name="l00875"></a><span class="lineno"> 875</span>  Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> &cloud_out);</div>
<div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  </div>
<div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00878"></a><span class="lineno"><a class="line" href="namespacepcl.html#a9f7d5505eb5192ddae706e461dc91c8b"> 878</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a>& indices,</div>
<div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  <span class="keyword">const</span> Eigen::Vector4f &centroid,</div>
<div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  Eigen::MatrixXf &cloud_out)</div>
<div class="line"><a name="l00882"></a><span class="lineno"> 882</span>  {</div>
<div class="line"><a name="l00883"></a><span class="lineno"> 883</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, float> (cloud_in, indices, centroid, cloud_out));</div>
<div class="line"><a name="l00884"></a><span class="lineno"> 884</span>  }</div>
<div class="line"><a name="l00885"></a><span class="lineno"> 885</span>  </div>
<div class="line"><a name="l00886"></a><span class="lineno"> 886</span>  <span class="keyword">template</span> <<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T> <span class="keywordtype">void</span></div>
<div class="line"><a name="l00887"></a><span class="lineno"><a class="line" href="namespacepcl.html#a593f079cc31336760d9e5b8a9b3ec5e4"> 887</a></span>  <a class="code" href="group__common.html#ga7f82fbd4e17063ab86287a2543bdea88">demeanPointCloud</a> (<span class="keyword">const</span> <a class="code" href="classpcl_1_1_point_cloud.html">pcl::PointCloud<PointT></a> &cloud_in,</div>
<div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_indices.html">pcl::PointIndices</a>& indices,</div>
<div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  <span class="keyword">const</span> Eigen::Vector4d &centroid,</div>
<div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  Eigen::MatrixXd &cloud_out)</div>
<div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  {</div>
<div class="line"><a name="l00892"></a><span class="lineno"> 892</span>  <span class="keywordflow">return</span> (demeanPointCloud<PointT, double> (cloud_in, indices, centroid, cloud_out));</div>
<div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  }</div>
<div class="line"><a name="l00894"></a><span class="lineno"> 894</span> <span class="comment"></span> </div>
<div class="line"><a name="l00895"></a><span class="lineno"> 895</span> <span class="comment"> /** \brief Helper functor structure for n-D centroid estimation. */</span></div>
<div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  <span class="keyword">template</span><<span class="keyword">typename</span> Po<span class="keywordtype">int</span>T, <span class="keyword">typename</span> Scalar></div>
<div class="line"><a name="l00897"></a><span class="lineno"><a class="line" href="structpcl_1_1_nd_centroid_functor.html"> 897</a></span>  <span class="keyword">struct </span><a class="code" href="structpcl_1_1_nd_centroid_functor.html">NdCentroidFunctor</a></div>
<div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  {</div>
<div class="line"><a name="l00899"></a><span class="lineno"><a class="line" href="structpcl_1_1_nd_centroid_functor.html#ae350f1a63879704c6eee84856283d56a"> 899</a></span>  <span class="keyword">using</span> <a class="code" href="structpcl_1_1_nd_centroid_functor.html#ae350f1a63879704c6eee84856283d56a">Pod</a> = <span class="keyword">typename</span> traits::POD<PointT>::type;</div>
<div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  </div>
<div class="line"><a name="l00901"></a><span class="lineno"><a class="line" href="structpcl_1_1_nd_centroid_functor.html#aa199ae32caa3d7c4d0ee7264f479f489"> 901</a></span>  <a class="code" href="structpcl_1_1_nd_centroid_functor.html#aa199ae32caa3d7c4d0ee7264f479f489">NdCentroidFunctor</a> (<span class="keyword">const</span> <a class="code" href="structpcl_1_1_point_x_y_z_r_g_b.html">PointT</a> &p, Eigen::Matrix<Scalar, Eigen::Dynamic, 1> &centroid)</div>
<div class="line"><a name="l00902"></a><span class="lineno"> 902</span>  : centroid_ (centroid),</div>
<div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  p_ (reinterpret_cast<const <a class="code" href="structpcl_1_1_nd_centroid_functor.html#ae350f1a63879704c6eee84856283d56a">Pod</a>&>(p)) { }</div>
<div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  </div>
<div class="line"><a name="l00905"></a><span class="lineno"><a class="line" href="structpcl_1_1_nd_centroid_functor.html#ab4b6eb31aba001d273d32662db003d71"> 905</a></span>  <span class="keyword">template</span><<span class="keyword">typename</span> Key> <span class="keyword">inline</span> <span class="keywordtype">void</span> <a class="code" href="structpcl_1_1_nd_centroid_functor.html#ab4b6eb31aba001d273d32662db003d71">operator() </a>()</div>
<div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  {</div>
<div class="line"><a name="l00907"></a><span class="lineno"> 907</span>  <span class="keyword">using</span> T = <span class="keyword">typename</span> pcl::traits::datatype<PointT, Key>::type;</div>
<div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  <span class="keyword">const</span> std::uint8_t* raw_ptr = <span class="keyword">reinterpret_cast<</span><span class="keyword">const </span>std::uint8_t*<span class="keyword">></span>(&p_) + pcl::traits::offset<PointT, Key>::value;</div>
<div class="line"><a name="l00909"></a><span class="lineno"> 909</span>  <span class="keyword">const</span> T* data_ptr = <span class="keyword">reinterpret_cast<</span><span class="keyword">const </span>T*<span class="keyword">></span>(raw_ptr);</div>
<div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  </div>
<div class="line"><a name="l00911"></a><span class="lineno"> 911</span>  <span class="comment">// Check if the value is invalid</span></div>
<div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  <span class="keywordflow">if</span> (!std::isfinite (*data_ptr))</div>
<div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  {</div>
<div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  f_idx_++;</div>
<div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  <span class="keywordflow">return</span>;</div>
<div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  }</div>
<div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  </div>
<div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  centroid_[f_idx_++] += *data_ptr;</div>
<div class="line"><a name="l00919"></a><span class="lineno"> 919</span>  }</div>
<div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  </div>
<div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  <span class="keyword">private</span>:</div>
<div class="line"><a name="l00922"></a><span class="lineno"> 922</span>  <span class="keywordtype">int</span> f_idx_{0};</div>
<div class="line"><a name="l00923"></a><span class="lineno"> 923</span>  Eigen::Matrix<Scalar, Eigen::Dynamic, 1> &centroid_;</div>
<div class="line"><a name="l00924"></a><span class="lineno"> 924</span>  <span class="keyword">const</span> <a class="code" href="structpcl_1_1_nd_centroid_functor.html#ae350f1a63879704c6eee84856283d56a">Pod</a> &p_;</div>
<div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  };</div>
<div class="line"><a name="l00926"></a><span class="lineno"> 926</span> <span class="comment"></span> </div>
<div class="line"><a name="l00927"></a><span class="lineno"> 927</span> <span class="comment"> /** \brief General, all purpose nD centroid estimation for a set of points using their</span></div>
<div class="line"><a name="l00928"></a><span class="lineno"> 928</span> <span class="comment"> * indices.</span></div>