Statistical models of face images--improving specificity
Journal
Image and Vision Computing
Date Issued
March 1998
DOI
10.1016/S0262-8856(97)00069-3
Abstract
Model-based approaches to the interpretation of face images have proved very successful. We have previously described statistically based models of face shape and grey-level appearance and shown how they can be used to perform various coding and interpretation tasks. In the paper we describe improved methods of modelling which couple shape and grey-level information more directly than our existing methods, isolate the changes in appearance due to different sources of variability (person, expression, pose, lighting) and deal with non-linear shape variation. We show that the new methods are better suited to interpretation and tracking tasks.