Enabled FAST feature detection on specific image locations

Some applications only want to know if there are feature at specific
locations. To fit these needs the FAST approach is extended in
FASTForPointSet to recieve a vector of locations and calculates the FAST
response on these positions. 
If it is below the threshold, it will be removed from the list.

Author: baudenri

modules/xfeatures2d/include/opencv2/xfeatures2d.hpp

@@ -259,6 +259,32 @@ class CV_EXPORTS_W DAISY : public Feature2D
 };
 
 
+
+/** @brief Estimates cornerness for prespecified KeyPoints using the FAST algorithm
+
+@param image grayscale image where keypoints (corners) are detected.
+@param keypoints keypoints which should be tested to fit the FAST criteria. Keypoints not beeing
+detected as corners are removed.
+@param threshold threshold on difference between intensity of the central pixel and pixels of a
+circle around this pixel.
+@param nonmaxSuppression if true, non-maximum suppression is applied to detected corners
+(keypoints).
+@param type one of the three neighborhoods as defined in the paper:
+FastFeatureDetector::TYPE_9_16, FastFeatureDetector::TYPE_7_12,
+FastFeatureDetector::TYPE_5_8
+
+Detects corners using the FAST algorithm by @cite Rosten06 .
+ */
+CV_EXPORTS void FASTForPointSet( InputArray image, CV_IN_OUT std::vector<KeyPoint>& keypoints,
+                      int threshold, bool nonmaxSuppression=true, int type=FastFeatureDetector::TYPE_9_16);
+
+
+void makeOffsets(int pixel[25], int row_stride, int patternSize);
+
+template<int patternSize>
+int cornerScore(const uchar* ptr, const int pixel[], int threshold);
+
+
 //! @}
 
 }