Facial Analysis From Continuous Video With Application to Human -Computer Interface

88 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 1999.The algorithm described in this thesis for embedded face and facial expression recognition is based on a novel probabilistic framework. In this novel framework, faces are modeled not only by their appearance, but also by the spatio-temporal deformation pattern of their expressions. Face recognition and facial expression recognition are carried out in a maximum likelihood setup. Given an image sequence, the algorithm finds the person's model and the facial expression that maximizes the likelihood probability of the observed images. In this framework, facial appearance matching is enhanced by facial expression modeling. Also, changes in facial features due to expressions are used together with facial deformation patterns to perform expression recognition.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD