Development of an eye system for three dimensional shape reconstruction

A three-dimensional vision system is indispensable for human-like robots and intelligent industrial robots. In order to reconstruct three dimensional shape of an object, an eye system is developed by combining stereo cameras and a laser stripe system based on the fact that two systems are complementary to each other. Pattern recognition algorithms for processing and fusion of sensor data are proposed. Edges and corner points (vertexes) of an object are extracted from stereo images, and surfaces constructing the object and edge points in intersections between neighbor surfaces are found from laser stripe images. Finally, each processed image is fused together for extracting three dimensional surface description. The proposed algorithms have been experimentally validated for polyhedral objects.

[1]  Rangachar Kasturi,et al.  Machine vision , 1995 .

[2]  Gérard G. Medioni,et al.  3-D Surface Description from Binocular Stereo , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Peter K. Allen,et al.  Integrating Vision and Touch for Object Recognition Tasks , 1988, Int. J. Robotics Res..

[4]  Takeo Kanade,et al.  Three-Dimensional Machine Vision , 1987 .

[5]  Tamio Arai,et al.  Fusion of range image and intensity image for 3D shape recognition , 1996, Proceedings of IEEE International Conference on Robotics and Automation.

[6]  Tamio Arai,et al.  Strategy and fundamental algorithms of fusing range image and intensity image for object recognition , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[7]  Daphna Weinshall,et al.  Qualitative Depth from Stereo, with Applications , 1990, Comput. Vis. Graph. Image Process..

[8]  Richard P. Wildes,et al.  Direct Recovery of Three-Dimensional Scene Geometry From Binocular Stereo Disparity , 1991, IEEE Trans. Pattern Anal. Mach. Intell..