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Robust Matching by Partial Correlation

Zhong-Dan Lan 1, 2 Roger Mohr 1, 2 Paolo Remagnino 2 
1 MOVI - Modeling, localization, recognition and interpretation in computer vision
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : Stereo matching by correlation near occlusions is a very challenging problem. When a partial occlusion occurs, most of the standard methods fail to produce acceptable results. This is because the techniques used do not take into account the presence of the occluding region. We propose a robust technique which we call partial correlation. This technique makes use of the least median square method which has recently been used for vision problems such as robust surface reconstruction. It performs better than standard methods near occlusions. It works by first of all disambiguating between the occluding region and the object region in the template and in the candidate window. A binary weighted correlation is then performed on the object regions. We present a comparative study between our approach and two other techniques. Experiment results validate our approach.
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Submitted on : Monday, December 20, 2010 - 8:44:16 AM
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  • HAL Id : inria-00548387, version 1



Zhong-Dan Lan, Roger Mohr, Paolo Remagnino. Robust Matching by Partial Correlation. British Machine Vision Conference (BMVC '95), Sep 1995, Birmingham, United Kingdom. pp.651--660. ⟨inria-00548387⟩



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