Pose-invariant face matching using MRF energy minimization framework

Abstract

A pose-invariant face verification system based on an image matching method is presented. The method uses the normalized energy of the established match between images as a measure of goodness-of-match. The method can tolerate moderate global spatial transformations between the gallery and the test images and alleviates the need for geometric and photometric normalization of facial images. It requires no training on non-frontal face images. A number of innovations, such as a dynamic block size and block shape adaptation, as well as label pruning and error prewhitening measures have been introduced to increase the effectiveness of the approach. The experimental evaluation of the method is performed on the rotation shots of the XM2VTS database and promising results are obtained. © 2009 Springer.