Publication

Combining color-based invariant gradient detector with HoG descriptors for robust image detection in scenes under cast shadows

Conference Article

Conference

IEEE International Conference on Robotics and Automation (ICRA)

Edition

2009

Pages

1997-2002

Doc link

http://dx.doi.org/10.1109/ROBOT.2009.5152429

File

Download the digital copy of the doc pdf document

Abstract

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.

Categories

computer vision.

Scientific reference

M. Villamizar, J. Scandaliaris, A. Sanfeliu and J. Andrade-Cetto. Combining color-based invariant gradient detector with HoG descriptors for robust image detection in scenes under cast shadows, 2009 IEEE International Conference on Robotics and Automation, 2009, Kobe, Japó, pp. 1997-2002, IEEE.