Combination of kernels applied to face verification

Authors:
Isaac Martín De Diego;Cristina Conde;Ángel Serrano;Enrique Cabello
Affiliations:
Face Recognition and Artificial Vision Group, Universidad Rey Juan Carlos, Móstoles, Spain;Face Recognition and Artificial Vision Group, Universidad Rey Juan Carlos, Móstoles, Spain;Face Recognition and Artificial Vision Group, Universidad Rey Juan Carlos, Móstoles, Spain;Face Recognition and Artificial Vision Group, Universidad Rey Juan Carlos, Móstoles, Spain
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

In this paper a novel method of information fusion at classifier level is applied to face verification. Three complementary kinds of facial data have been considered: texture, range data and curvature images. Three different kernels have been defined from each representation and finally a combined kernel has been developed. The resulting kernel has been used to train a classifier based on Support Vector Machines and it has been applied to face verification. The method has been deeply tested using the Face Recognition Grand Challenge database. The experiments show that in all cases the combined proposed classifier improves individual classifiers.