Optimal Gabor kernel location selection for face recognition

In local feature?based face recognition systems, the topographical locations of feature extractors directly affect the discriminative power of a recognizer. Better recognition accuracy can be achieved by the determination of the positions of salient image locations. Most of the facial feature selection algorithms in the literature work with two assumptions: one, that the importance of each feature is independent of the other features, and two, that the kernels should be located at fiducial points. Under these assumption, one can only get a sub?optimal solution. In this paper, we present a methodology that tries to overcome this problem by relaxing the two assumptions using a formalism of subset selection problem. We use a number of feature selection algorithms and a genetic algorithm. Comparative results on the FERET dataset confirm the viability of our approach.

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Berk Gökberk, Ethem Alpaydin, Lale Akarun, M. Okan Irfanoglu
• Keywords: Facial Feature Selection, Feature Extractors, Feature Selection Algorithms, ICIP 2003, Image Processing, Salient Image Locations, Subset Selection Problem