PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Disambiguating multi-modal scene representations using perceptual grouping constraints
Nicolas Pugeault, Florentin Woergoetter and Norbert Krueger
PLoS ONE Volume 5, Number 6, 2010. ISSN 1932-6203

Abstract

In its early stages, the visual system suffers from a lot of ambiguity and noise that severely limits the performance of early vision algorithms. This article presents feedback mechanisms between early visual processes, such as perceptual grouping, stereopsis and depth reconstruction, that allow the system to reduce this ambiguity and improve early representation of visual information. In the first part, the article proposes a local perceptual grouping algorithm that — in addition to commonly used geometric information — makes use of a novel multi–modal measure between local edge/line features. The grouping information is then used to: 1) disambiguate stereopsis by enforcing that stereo matches preserve groups; and 2) correct the reconstruction error due to the image pixel sampling using a linear interpolation over the groups. The integration of mutual feedback between early vision processes is shown to reduce considerably ambiguity and noise without the need for global constraints.

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EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:7169
Deposited By:Nicolas Pugeault
Deposited On:07 March 2011