Object categorization with SVM: kernels for local features

Eichhorn, J; Chapelle, O

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Object categorization with SVM: kernels for local features

Eichhorn, J., & Chapelle, O.(2004). Object categorization with SVM: kernels for local features (137).

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-D8B5-C Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-D8B6-A

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Creators:
Eichhorn, J^{1, 2}, Author
Chapelle, O¹, Author

Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795
2Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805

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Abstract: 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.

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Dates: Date issued: 2004-07

Publication Status: Issued

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Identifiers: Report Nr.: 137
BibTex Citekey: 2778

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