The intermediate matching kernel for image local features

Sabri Boughorbel, Jean Philippe Tarel, Nozha Boujemaa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

32 Citations (Scopus)

Abstract

We introduce the Intermediate Matching (IM) kernel for SVM-based object recognition. The IM kernel operates on a feature space of vector sets where each image is represented by a set of local features. Matching algorithms have proved to be efficient for such types of features. Nevertheless, kernelizing the matching for SVM does not lead to positive definite kernels. The IM kernel overcomes this drawback, as it mimics matching algorithms while being positive definite. The IM kernel introduces an intermediary set of so-called virtual local features. These select the pairs of local features to be matched. Comparisons with the Matching kernel shows that the IM kernels leads to similar performances.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks, IJCNN 2005
Pages889-894
Number of pages6
Volume2
DOIs
Publication statusPublished - 2005
Externally publishedYes
EventInternational Joint Conference on Neural Networks, IJCNN 2005 - Montreal, QC, Canada
Duration: 31 Jul 20054 Aug 2005

Other

OtherInternational Joint Conference on Neural Networks, IJCNN 2005
CountryCanada
CityMontreal, QC
Period31/7/054/8/05

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ASJC Scopus subject areas

  • Software

Cite this

Boughorbel, S., Tarel, J. P., & Boujemaa, N. (2005). The intermediate matching kernel for image local features. In Proceedings of the International Joint Conference on Neural Networks, IJCNN 2005 (Vol. 2, pp. 889-894). [1555970] https://doi.org/10.1109/IJCNN.2005.1555970