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Proceedings Paper

Robust regression in computer vision
Author(s): Peter Meer; Doron Mintz
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Paper Abstract

We describe the least median of squares (LMedS) robust estimator which identifies the surface corresponding to the absolute majority of the data points. However when all the data points are corrupted by noise LMedS may fail. This is the case in computer vision applications and we have developed a new approach which preserves the robustness of LMedS but avoids its artifacts in the presence of noise.

Paper Details

Date Published: 1 February 1991
PDF: 12 pages
Proc. SPIE 1381, Intelligent Robots and Computer Vision IX: Algorithms and Techniques, (1 February 1991); doi: 10.1117/12.25173
Show Author Affiliations
Peter Meer, Univ. of Maryland (United States)
Doron Mintz, Univ. of Maryland (United States)

Published in SPIE Proceedings Vol. 1381:
Intelligent Robots and Computer Vision IX: Algorithms and Techniques
David P. Casasent, Editor(s)

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