Share Email Print
cover

Proceedings Paper

Trinocular stereovision by matching in parameter space
Author(s): Jun Shen; Philippe Paillou
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

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)

© SPIE. Terms of Use
Back to Top