Lab Meeting 12 May 2007 (Vincent): Face recognition Using Probabilistic Eigenface

In this talk, I will present a face recognition approach that integrates eigenface with probabilistic aprroach. I'll also demonstrate some result using this approach.

This work is based on the following paper.

Title : Beyond eigenfaces: probabilistic matching for face recognition

Author : Moghaddam, B. Wahid, W. Pentland, A.

Abstract :
We propose a technique for direct visual matching for face recognition and database search, using a probabilistic measure of similarity which is based on a Bayesian analysis of image differences. Specifically we model lure mutually exclusive classes of variation between facial images: intra-personal (variations in appearance of the same individual, due to different expressions or lighting) and extra-personal (variations in appearance due to a difference in identity). The likelihoods for each respective class are learned from training data using eigenspace density estimation and used to compute similarity based on the a posteriori probability of membership in the intra-personal class, and ultimately used to rank matches in the database. The performance advantage of this probabilistic technique over nearest-neighbor eigenface matching is demonstrated using results front ARPA's 1996 “FERET” face recognition competition, in which this algorithm was found to be the top performer.

Here is the full text.