In the problem of object category recognition, we have studied different families of descriptors exploiting RGB and 3D information. Furthermore, we have proven practically that 3D shape-based descriptors are more suitable for this type of recognition due to low shape intra-class variance, as opposed to image texture-based. In addition, we have also shown how an efficient Naive Bayes Nearest Neighbor (NBNN) classifier can scale to a large hierarchical RGB-D Object Dataset [2] and achieve, with a single descriptor type, an accuracy close to state-of-art learning based approaches using combined descriptors.

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information,Intra class,Learning-based approach,Naive bayes,Nearest neighbors,Object category recognition,Shape based,Shape descriptors

• Ciências da Computação e da Informação - Ciências Naturais
• Engenharia Eletrotécnica, Eletrónica e Informática - Engenharia e Tecnologia