The GCS kernel for SVM-based image recognition

Authors:
Sabri Boughorbel;Jean-Philippe Tarel;François Fleuret;Nozha Boujemaa
Affiliations:
INRIA Rocquencourt, Le Chesnay, France;DESE, LCPC, Paris, France;CVLAB, EPFL, Lausanne, Switzerland;INRIA Rocquencourt, Le Chesnay, France
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial neural networks: formal models and their applications - Volume Part II
Year:
2005

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Abstract

In this paper, we present a new compactly supported kernel for SVM based image recognition. This kernel which we called Geometric Compactly Supported (GCS) can be viewed as a generalization of spherical kernels to higher dimensions. The construction of the GCS kernel is based on a geometric approach using the intersection volume of two n-dimensional balls. The compactness property of the GCS kernel leads to a sparse Gram matrix which enhances computation efficiency by using sparse linear algebra algorithms. Comparisons of the GCS kernel performance, for image recognition task, with other known kernels prove the interest of this new kernel.