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Título: | Robust color contour object detection invariant to shadows |
Autor: | Scandaliaris, Jorge CSIC; Villamizar, Michael CSIC; Andrade-Cetto, Juan CSIC ORCID ; Sanfeliu, Alberto CSIC ORCID | Palabras clave: | Color invariance Shadow removal Object detection Boosting Computer vision |
Fecha de publicación: | 2007 | Editor: | Springer Nature | Citación: | Progress in Pattern Recognition, Image Analysis and Applications: 301-310 (2007) | Serie: | Lecture Notes in Computer Science 4756 | Resumen: | 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. | Descripción: | Presentado al 12th Iberoamerican Congress on Pattern Recognition (CIARP-2007) celebrado en Valparaiso (Chile) del 13 al 16 de noviembre. | Versión del editor: | http://dx.doi.org/10.1007/978-3-540-76725-1_32 | URI: | http://hdl.handle.net/10261/30345 | DOI: | 10.1007/978-3-540-76725-1_32 | ISBN: | 978-3-540-76724-4 |
Aparece en las colecciones: | (IRII) Libros y partes de libros |
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Robust color contour.pdf | 611,38 kB | Adobe PDF | Visualizar/Abrir |
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