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Proceedings Paper

Trinocular stereovision by generalized Hough transform
Author(s): Jun Shen; Philippe Paillou
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Paper Abstract

In this paper, we present the generalized Hough transform to match the edge segments in trinocular stereovision. We show that the corresponding segment triplet candidates can be detected by a generalized Hough transform in the parameter space ((theta) ,(phi) ) which characterizes the 3D segment orientation. These triplets can then be verified, and the position parameters of the 3D segments can be detected by a generalized Hough transform in the parameter space (Y,Z). So the matching of geometric primitives in trinocular stereovision images can be found by the cascade of two generalized Hough transforms in the spaces of only two dimensions. Experimental results are reported also. Our method shows the following advantages: (1) Trinocular stereovision image matching is transformed into Hough transforms in 2D parameter spaces, which reduces much 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 3D 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: 3 October 1995
PDF: 9 pages
Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222689
Show Author Affiliations
Jun Shen, Institut de Geodynamique (France)
Philippe Paillou, Institut de Geodynamique (France)


Published in SPIE Proceedings Vol. 2588:
Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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