Object categorization with SVM: kernels for local features
2004
Technical Report
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In this paper, we propose to combine an efficient image representation based on local descriptors with a Support Vector Machine classifier in order to perform object categorization. For this purpose, we apply kernels defined on sets of vectors. After testing different combinations of kernel / local descriptors, we have been able to identify a very performant one.
Author(s): | Eichhorn, J. and Chapelle, O. |
Number (issue): | 137 |
Year: | 2004 |
Month: | July |
Day: | 0 |
Department(s): | Empirical Inference |
Bibtex Type: | Technical Report (techreport) |
Institution: | Max Planck Institute for Biological Cybernetics, Tübingen, Germany |
Digital: | 1 |
Organization: | Max-Planck-Gesellschaft |
School: | Biologische Kybernetik |
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BibTex @techreport{2778, title = {Object categorization with SVM: kernels for local features}, author = {Eichhorn, J. and Chapelle, O.}, number = {137}, organization = {Max-Planck-Gesellschaft}, institution = {Max Planck Institute for Biological Cybernetics, Tübingen, Germany}, school = {Biologische Kybernetik}, month = jul, year = {2004}, doi = {}, month_numeric = {7} } |