With the recent emphasis on homeland security, there is an increased interest in accurate and non-invasive techniques for face recognition. Most of the current techniques perform a structural analysis of facial features from still images. In this project, we propose a new method for face recognition, which is based on dynamic instead of static facial features. We use a new marker-less approach which tracks the motion of natural markers on the face, such as skin pores, from two subsequent high-resolution images. We track these during a facial expression, such as a subtle smile, and obtain a vector field that characterizes the deformation of the face. Since it is almost impossible to imitate another person's facial expressions these deformation fields are bound to be unique to an individual. (This is a joint project between Stony Brook University (SUNY) and New York State Strategic Center for Port and Maritime Security, SUNY Maritime.)

Dynamic Approach for Face Recognition using Digital Image Skin Correlation S. Pamudurthy, E Guan, K. Mueller, and M. Rafailovich Audio- and Video-based Biometric Person Authentication (AVBPA) 2005 New York, July 2005