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Publication Detailed Description
Advances in visual computing: 9th International Symposium, ISVC 2013, Proceedings
Year (definitive publication)
2013
Language
English
Country
Germany
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Abstract
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.
Acknowledgements
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Keywords
information,Intra class,Learning-based approach,Naive bayes,Nearest neighbors,Object category recognition,Shape based,Shape descriptors
Fields of Science and Technology Classification
- Computer and Information Sciences - Natural Sciences
- Electrical Engineering, Electronic Engineering, Information Engineering - Engineering and Technology
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