Estimation of facial expression intensity from a sequence of binary face images

This paper presents a method of estimation of facial expression intensity from a sequence of binary facial images obtained from video. The binarization has been done using a neuro-visual model of figure ground segregation. The Local Binary Pattern (LBP) is taken as characteristic feature of a face with expression. This pattern gets evolved in the temporal domain over the sequence. The dynamics of the pattern, starting from a neutral face, is characterised by Hausdorff distance. Back Propagation (BP) Neural Networks are trained to estimate the expression intensity level of the basic expressions.