Publication
Robust color contour object detection invariant to shadows
Conference Article
Conference
Iberoamerican Congress on Pattern Recognition (CIARP)
Edition
12th
Pages
301-310
Doc link
http://dx.doi.org/10.1007/978-3-540-76725-1_32
File
Abstract
In this work a new robust color and contour based object detection method in images with varying shadows is presented. The method relies on a physics-based contour detector that emphasizes material changes and a contour-based boosted classifier. The method has been tested in a sequence of outdoor color images presenting varying shadows using two classifiers, one that learns contour object features from a simple gradient detector, and another that learns from the photometric invariant contour detector. It is shown that the detection performance of the classifier trained with the photometric invariant detector is significantly higher than that of the classifier trained with gradient detector.
Categories
computer vision.
Author keywords
color invariance, shadow removal, object detection, boosting
Scientific reference
J. Scandaliaris, M. Villamizar, J. Andrade-Cetto and A. Sanfeliu. Robust color contour object detection invariant to shadows, 12th Iberoamerican Congress on Pattern Recognition, 2007, Valparaiso, Xile, in Progress in Pattern Recognition, Image Analysis and Applications, Vol 4756 of Lecture Notes in Computer Science, pp. 301-310, 2008, Springer Verlag, Berlin, Alemanya.
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