Trinocular stereovision by matching in parameter space

Jun Shen; Philippe Paillou

doi:10.1117/12.217459

28 August 1995 Trinocular stereovision by matching in parameter space

Jun Shen, Philippe Paillou

Proceedings Volume 2620, International Conference on Intelligent Manufacturing; (1995) https://doi.org/10.1117/12.217459
Event: International Conference on Intelligent Manufacturing, 1995, Wuhan, China

Abstract

In this paper, we generalize the Hough transform to match the edge segments in trinocular stereovision and to determine the parameters of the segments in 3-D space. We show that the corresponding segment triplet candidates can be detected by a Hough transform in the parameter plane ((theta) , (phi) ) which characterizes the 3-D segment orientation. These triplets can then be verified, and the position parameters of the 3-D segments can be detected by a Hough transform in the parameter plane (Y, Z). So the matching of geometric primitives in trinocular stereovision images can be found by the cascade of searchings in two 2-D parameter spaces only. Experimental results are satisfactory. Our method shows the following advantages: (1) Trinocular stereovision image matching is transformed into searching in 2-D parameter spaces, which much reduces the computational complexity. (2) Matching can be done completely in parallel. (3) No a priori similarity between images is needed, so very different views can be used, which improves the precision of 3-D reconstruction. (4) It is very efficient to solve false targets. (5) Our method gives good results even for partially hidden segments.

Citation Download Citation

Jun Shen and Philippe Paillou "Trinocular stereovision by matching in parameter space", Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); https://doi.org/10.1117/12.217459

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