How to Combine Color and Shape Information for 3D Object Recognition: Kernels Do the Trick
Abstract
This paper presents a kernel method that allows to combine color and shape information for appearance-based object recognition. It doesn't require to define a new common representation, but use the power of kernels to combine different representations together in an effective manner. These results are achieved using results of statis(cid:173) tical mechanics of spin glasses combined with Markov random fields via kernel functions. Experiments show an increase in recognition rate up to 5.92% with respect to conventional strategies.
Cite
Text
Caputo and Dorkó. "How to Combine Color and Shape Information for 3D Object Recognition: Kernels Do the Trick." Neural Information Processing Systems, 2002.Markdown
[Caputo and Dorkó. "How to Combine Color and Shape Information for 3D Object Recognition: Kernels Do the Trick." Neural Information Processing Systems, 2002.](https://mlanthology.org/neurips/2002/caputo2002neurips-combine/)BibTeX
@inproceedings{caputo2002neurips-combine,
title = {{How to Combine Color and Shape Information for 3D Object Recognition: Kernels Do the Trick}},
author = {Caputo, B. and Dorkó, Gy.},
booktitle = {Neural Information Processing Systems},
year = {2002},
pages = {1399-1406},
url = {https://mlanthology.org/neurips/2002/caputo2002neurips-combine/}
}