A method of stereo vision matching based on OpenCV

Stereo vision is an important branch of the research area in computer vision. Among the techniques of stereo vision, binocular stereo vision which is based on processing two images remains a research hotspot. Binocular stereo vision directly simulates the manner of human eyes observing one scene from two different viewpoints. By using the principle of triangulation, the disparities of a number of 3D points mapped to pixels in two images are computed. Then the visual information of depth is also recovered. The object surface shape can be acquired using these disparities. In this paper, a pair of common web cameras is used to collect images. Based on OpenCV, the calibration algorithm of stereo vision is achieved. Stereo rectify and stereo matching algorithm are also rapidly and efficiently implemented. Finally, the depth information of object is obtained.

[1]  Richard Szeliski,et al.  A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms , 2001, International Journal of Computer Vision.

[2]  Takeo Kanade,et al.  Visual hull alignment and refinement across time: a 3D reconstruction algorithm combining shape-from-silhouette with stereo , 2003, 2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings..

[3]  Pietro Perona,et al.  Local Analysis for 3D Reconstruction of Specular Surfaces - Part II , 2002, ECCV.

[4]  Martin A. Fischler,et al.  Computational Stereo , 1982, CSUR.

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

[6]  Lawrence G. Roberts,et al.  Machine Perception of Three-Dimensional Solids , 1963, Outstanding Dissertations in the Computer Sciences.