Depth Error Estimation of Static RGBD Sensors

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This project allows computing the error in static RGB-D sensors. The code is the implementation of the papers: A Versatile Method for Depth Data Error Estimation in RGB-D Sensors and Depth Data Error Modeling of the ZED 3D Vision Sensor From Stereolabs.

Installation:

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Dependences (mandatory):

• Eigen3
• OpenCV: tested with version 3.4.1.

Download code and open a terminal ctrl+t:

$ cd path 
$ mkdir build & cd build 
$ cmake .. 
$ make

How to use:

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• Run: ./depth_error <save_windows> <device> <devide_resolution>

• Inputs:

  • <save_windows>: set 1 to save the pictures of the PCL 3D visualizer with the point clouds used to the depth error. Or choose 0 to save nothing.
  • <device>: choose the sensor to be evaluated, can be 1 for the Stereolabs ZED camera or 2 for Kinect
  • <devide_resolution>: choose the resolution of the device that you use, for example: 4 for ZED (672x376 px), 5 for Kinect version 1 (640x480 px) and 6 for Kinect version 2 (512x424 px). Remember that the Kinect version 2 has two resolutions, (1920x1080) and (512x424 px). We use the minor resolution because it is more similar to the other devices' resolutions, i.e., to make the comparison of the devices fairer.

• Outputs:

  • built/Results/: a folder that contains the pictures of the PCL 3D visualizer with the point clouds used to the depth error.
  • Table_<devide_resolution>.txt: .txt file with two columns, the first one represents the depth in millimeters, and the second one represents the RMSE error for this depth.

• Example:

  $ ./depth_error 1 1 4 
  

References:

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Please cite the following papers if use this code and A Versatile Method for Depth Data Error Estimation in RGB-D Sensors:

@Article{Ortiz20182,
    AUTHOR = {Ortiz, Luis E. and Cabrera, Elizabeth V. and Silva, Bruno M. F. da and Clua, Esteban W. G. and Gonçalves, Luiz M. G.},
    TITLE = {A Versatile Method for Depth Data Error Estimation in RGB-D Sensors},
    JOURNAL = {Sensors},
    VOLUME = {18},
    YEAR = {2018},
    NUMBER = {9},
    ARTICLE-NUMBER = {3122},
    URL = {https://www.mdpi.com/1424-8220/18/9/3122},
    ISSN = {1424-8220},
    DOI = {10.3390/s18093122}
}

@ARTICLE{Ortiz2018,
    TITLE   = {Depth data error modeling of the ZED 3D vision sensor from stereolabs},
    AUTHOR  = {Ortiz, Luis Enrique and Cabrera, Elizabeth V and Gon{\c{c}}alves, Luiz M},
    JOURNAL = {ELCVIA: electronic letters on computer vision and image analysis},
    VOLUME  = {17},
    NUMBER  = {1},
    PAGES   = {0001--15},
    YEAR    = {2018},
    DOI     = {https://doi.org/10.5565/rev/elcvia.1084},
    eISSN   = {1577-5097} 
}

NOTE:

If you find any of these codes helpful, please share my GitHub and STAR ⭐ this repository to help other enthusiasts to find these tools. Remember, the knowledge must be shared. Otherwise, it is useless and lost in time.