Empirical Inference
Technical Report
2004
Object categorization with SVM: kernels for local features
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}
}