Inclusion of local color information in generic object recognition is ignored by almost all approaches, although it is important and can improve the recognition performance. In this paper, we present a generic object recognition approach using boosting as a learning technique. Simple local color descriptors combined with the SIFT descriptors are used. Experiments using benchmark and complex generic object datasets are performed, and good performance is obtained.
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