Efficiently estimating facial expression and illumination in appearance-based tracking
José M. Buenaposada, Enrique Muñoz, Luis Baumela · 2006
We introduce a subspace representation of face appearance which separates facial expressions from illumination variations. The appearance of a face is represented by the addition of two approximately independent linear subspaces modelling facial expressions and illumination respectively. The independence assumption notably simplifies the training of the system. We only require two image sequences. One in which one facial expression is subject to all possible illuminations and another in which the face, under one illumination, performs all facial expressions. This simple model enables us to train the system with no manual intervention. We also introduce an efficient procedure for fitting this model, which can be used for tracking a human face in real-time. 1