Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/30099
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Título : Combining color-based invariant gradient detector with HoG descriptors for robust image detection in scenes under cast shadows
Autor : Villamizar, Michael, Scandaliaris, Jorge, Sanfeliu, Alberto, Andrade-Cetto, J.
Palabras clave : Computer vision
Fecha de publicación : 2009
Editor: Institute of Electrical and Electronics Engineers
Resumen: In this work we present a robust detection method in outdoor scenes under cast shadows using color based invariant gradients in combination with HoG local features. The method achieves good detection rates in urban scene classification and person detection outperforming traditional methods based on intensity gradient detectors which are sensible to illumination variations but not to cast shadows. The method uses color based invariant gradients that emphasize material changes and extract relevant and invariant features for detection while neglecting shadow contours. This method allows to train and detect objects and scenes independently of scene illumination, cast and self shadows. Moreover, it allows to do training in one shot, that is, when the robot visits the scene for the first time.
Descripción : Trabajo presentado al ICRA 2009 celebrado en Kobe (Japón) del 12 al 17 de mayo.
Versión del editor: http://dx.doi.org/10.1109/ROBOT.2009.5152429
URI : http://hdl.handle.net/10261/30099
ISBN : 978-1-4244-2788-8
DOI: 10.1109/ROBOT.2009.5152429
Citación : IEEE International Conference on Robotics and Automation: 1997-2002 (2009)
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