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Proceedings Paper

Using viewpoint consistency in active stereo vision
Author(s): James J. Clark; Michael J. Weisman; Alan L. Yuille
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Paper Abstract

Surface models embedded in Bayesian or regularization style stereo vision algorithms bias the solution in a nonviewpoint invariant way. This lack of invariance reveals itself when the surface is computed from different viewpoints. Using the consistency between views one can try to adapt the prior surface models in a way that renders them more viewpoint invariant. The goal is to be able to adapt the stereo algorithm over time so that the same surface shape is obtained from different views. The method described in this paper uses the surface consistency measure to choose between the solutions provided by a set of simple prior surface models.

Paper Details

Date Published: 1 November 1992
PDF: 7 pages
Proc. SPIE 1825, Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision, (1 November 1992); doi: 10.1117/12.131573
Show Author Affiliations
James J. Clark, Harvard Univ. (United States)
Michael J. Weisman, Harvard Univ. (United States)
Alan L. Yuille, Harvard Univ. (United States)


Published in SPIE Proceedings Vol. 1825:
Intelligent Robots and Computer Vision XI: Algorithms, Techniques, and Active Vision
David P. Casasent, Editor(s)

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