Zhou S.K., Chellappa R., Zhao W. Unconstrained face recognition

New York: Springer, 2006. — 243 p.The goal of this book is to provide a comprehensive review of unconstrained face recognition, especially face recognition from video, and to assemble descriptions of novel approaches that are able to recognize human faces under various unconstrained situations. The underlying theme of these approaches is that, unlike conventional face recognition algorithms, they exploit the inherent characteristics of the unconstrained situation and gain improvements in recognition performance when compared with conventional algorithms. For instance, generalized photometric stereo combines physics-based illumination model with statistical modeling to address face recognition under illumination variation. Simultaneous tracking and recognition employs the temporal information embedded in a video sequence and thus improves both tracking accuracy and recognition performance.