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Proceedings Paper

Trinocular stereovision by matching in parameter space
Author(s): Jun Shen; Philippe Paillou
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Paper 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.

Paper Details

Date Published: 28 August 1995
PDF: 8 pages
Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); doi: 10.1117/12.217459
Show Author Affiliations
Jun Shen, Univ. de Bordeaux III (France)
Philippe Paillou, Univ. de Bordeaux III (France)

Published in SPIE Proceedings Vol. 2620:
International Conference on Intelligent Manufacturing
Shuzi Yang; Ji Zhou; Cheng-Gang Li, Editor(s)

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