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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

Links: PDF

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},
  month_numeric = {7}
}