SVM-based obstacles recognition for road vehicle applications

Authors:
M. A. Sotelo;J. Nuevo;D. Fernandez;I. Parra;L. M. Bergasa;M. Ocana;R. Flores
Affiliations:
Department of Electronics, University of Alcala, Alcala de Henares, Madrid, Spain;Department of Electronics, University of Alcala, Alcala de Henares, Madrid, Spain;Department of Electronics, University of Alcala, Alcala de Henares, Madrid, Spain;Department of Electronics, University of Alcala, Alcala de Henares, Madrid, Spain;Department of Electronics, University of Alcala, Alcala de Henares, Madrid, Spain;Department of Electronics, University of Alcala, Alcala de Henares, Madrid, Spain;Department of Electronics, University of Alcala, Alcala de Henares, Madrid, Spain
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

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Abstract

This paper describes an obstacle Recognition System based on SVM and vision. The basic components of the detected objects are first located in the image and then combined with a SVM-based classifier. A distributed learning approach is proposed in order to better deal with objects variability, illumination conditions, partial occlusions and rotations. A large database containing thousands of object examples extracted from real road images has been created for learning purposes. We present and discuss the results achieved up to date.