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.
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Martínez-Gómez, J., Jiménez-Picazo, A., Gámez, J.A., García-Varea, I. (2010). Combining Image Invariant Features and Clustering Techniques for Visual Place Classification. In: Ünay, D., Çataltepe, Z., Aksoy, S. (eds) Recognizing Patterns in Signals, Speech, Images and Videos. ICPR 2010. Lecture Notes in Computer Science, vol 6388. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17711-8_21
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DOI: https://doi.org/10.1007/978-3-642-17711-8_21
Publisher Name: Springer, Berlin, Heidelberg
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