Combining image invariant features and clustering techniques for visual place classification

Authors:
Jesús Martínez-Gómez;Alejandro Jiménez-Picazo;José A. Gámez;Ismael García-Varea
Affiliations:
Computing Systems Department, SIMD i³A, University of Castilla-la Mancha, Albacete, Spain;Computing Systems Department, SIMD i³A, University of Castilla-la Mancha, Albacete, Spain;Computing Systems Department, SIMD i³A, University of Castilla-la Mancha, Albacete, Spain;Computing Systems Department, SIMD i³A, University of Castilla-la Mancha, Albacete, Spain
Venue:
ICPR'10 Proceedings of the 20th International conference on Recognizing patterns in signals, speech, images, and videos
Year:
2010

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Abstract

This paper presents the techniques developed by the SIMD group and the results obtained for the 2010 RobotVision task in the ImageCLEF competition. The approach presented tries to solve the problem of robot localization using only visual information. The proposed system presents a classification method using training sequences acquired under different lighting conditions. Well-known SIFT and RANSAC techniques are used to extract invariant points from the images used as training information. Results obtained in the RobotVision@ ImageCLEF competition proved the goodness of the proposal.