A probabilistic model of face mapping with local transformations and its application to person recognition

Perronnin, Florent;Dugelay, Jean-Luc;Rose, Kenneth W
IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), Volume 27, Issue 7, July 2005

This paper proposes a new measure of ?distance? between faces. This measure involves the estimation of the set of possible transformations between face images of the same person. The global transformation, which is assumed to be too complex for direct modeling, is approximated by a patchwork of local transformations, under a constraint imposing consistency between neighboring local transformations. The proposed system of local transformations and neighboring constraints is embedded within the probabilistic framework of a two-dimensional hidden Markov model. More specifically, we model two types of intra-class variabilities involving variations in facial expressions and illumination, respectively. The performance of the resulting method is assessed on a large data set consisting of four face databases. In particular, it is shown to outperform a leading approach to face recognition, namely, the Bayesian intra-/extra-personal classifier.

Digital Security
Eurecom Ref:
© 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PERMALINK : https://www.eurecom.fr/publication/1551