Affine trackability aids obstacle detection

Potential obstacles in the path of a mobile robot that can often be characterized as shallow (i.e., their extent in depth is small compared to their distance from the camera) are considered. The constraint of affine trackability is applied to automatic identification and 3-D reconstruction of shallow structures in realistic scenes. It is shown how this approach can handle independent object motion, occlusion, and motion discontinuity. Although the reconstructed structure is only a frontal plane approximation to the corresponding real structure, the robustness of depth of the approximation might be useful for obstacle avoidance, where the exact shape of an object may not be of consequence so long as collisions with it can be avoided.<<ETX>>

[1]  Narendra Ahuja,et al.  Motion and Structure From Two Perspective Views: Algorithms, Error Analysis, and Error Estimation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  James L. Crowley,et al.  Measuring Image Flow By Tracking Edge-lines , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[3]  Edward M. Riseman,et al.  Token-based extraction of straight lines , 1989, IEEE Trans. Syst. Man Cybern..

[4]  Rachid Deriche,et al.  Tracking line segments , 1990, Image Vis. Comput..

[5]  P. Mahalanobis On the generalized distance in statistics , 1936 .

[6]  Allen R. Hanson,et al.  Translating Optical Flow Into Token Matches And Depth From Looming , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[7]  Allen R. Hanson,et al.  Identification and 3D description of 'shallow' environmental structure in a sequence of images , 1991, Proceedings. 1991 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[8]  Yehezkel Lamdan,et al.  Object recognition by affine invariant matching , 2011, Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Y. Bar-Shalom Tracking and data association , 1988 .