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Título

Robust color contour object detection invariant to shadows

AutorScandaliaris, Jorge CSIC; Villamizar, Michael CSIC; Andrade-Cetto, Juan CSIC ORCID ; Sanfeliu, Alberto CSIC ORCID
Palabras claveColor invariance
Shadow removal
Object detection
Boosting
Computer vision
Fecha de publicación2007
EditorSpringer Nature
CitaciónProgress in Pattern Recognition, Image Analysis and Applications: 301-310 (2007)
SerieLecture Notes in Computer Science 4756
ResumenIn 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.
DescripciónPresentado al 12th Iberoamerican Congress on Pattern Recognition (CIARP-2007) celebrado en Valparaiso (Chile) del 13 al 16 de noviembre.
Versión del editorhttp://dx.doi.org/10.1007/978-3-540-76725-1_32
URIhttp://hdl.handle.net/10261/30345
DOI10.1007/978-3-540-76725-1_32
ISBN978-3-540-76724-4
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