Institute Homepage DE Sign In

Back

Empirical Inference Technical Report 2004

Object categorization with SVM: kernels for local features

no image
Empirical Inference
Jan Eichhorn
no image
Empirical Inference
Olivier Chapelle

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
Bibtex Type: Technical Report (techreport)
Digital: 1
Electronic Archiving: grant_archive
Institution: Max Planck Institute for Biological Cybernetics, Tübingen, Germany
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik
Links:

BibTex 

@techreport{2778,
  title = {Object categorization with SVM: kernels for local features},
  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.},
  number = {137},
  organization = {Max-Planck-Gesellschaft},
  institution = {Max Planck Institute for Biological Cybernetics, Tübingen, Germany},
  school = {Biologische Kybernetik},
  month = jul,
  year = {2004},
  slug = {2778},
  author = {Eichhorn, J. and Chapelle, O.},
  month_numeric = {7}
}