A Study of Image Processing Based Object Depth Estimation

Issue of object's depth estimation from binocular vision technique is studied in this paper. A binocular vision platform is set up to detect and estimate the object's depth. Mathematical derivation of object's depth from the two cameras of the proposed platform is re-visited to reveal the linkage between system parameters such as focal length and the estimation error. Both of simulation and experimental results are obtained for parametric analysis of estimation error. A comparison with Kinect is also given to demonstrate the superiority of the proposed design.

[1]  Andreas Geiger,et al.  Vision meets robotics: The KITTI dataset , 2013, Int. J. Robotics Res..

[2]  Zhengyou Zhang,et al.  A Flexible New Technique for Camera Calibration , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Chi-Yi Tsai,et al.  Face Tracking Interaction Control of a Nonholonomic Mobile Robot , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[4]  Jake K. Aggarwal,et al.  Quantization error in stereo imaging , 1988, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[5]  Long Yan,et al.  Research on 3D measuring based binocular vision , 2014, 2014 IEEE International Conference on Control Science and Systems Engineering.