Face posture estimation using eigen analysis on an IBR (image based rendered) database

In this paper, we present a novel representation of the human face for esti mating the orientation of the human head in a two dimensional intensity ima ge. The method combines the use of the much familiar eigenvalue based dissi milarity measure with image based rendering. There are two main components of the algorithm described here: the offline hierarchical image database ge neration and organization, and the online pose estimation stage. The synthe tic images of the subject's face are automatically generated offline, for a large set of pose parameter values, using an affine coordinate based image reprojection technique. The resulting database is formally called as the I BR (or image based rendered) database. This is followed by the hierarchical organization of the database, which is driven by the eigenvalue based diss imilarity measure between any two synthetic image pair. This hierarchically organized database is a detailed, yet structured, representation of the su bject's face. During the pose estimation of a subject in an image, the eige nvalue based measure is invoked again to search the synthetic (IBR) image c losest to the real image. This approach provides a relatively easy first st ep to narrow down the search space for complex feature detection and tracki ng algorithms in potential applications like virtual reality and video-tele conferencing applications. (C) 2001 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.