Feature Tracking and Expression Recognition of Face Using Dynamic Bayesian Network

Abstract- The human face plays a central role in social interaction, hence it is not surprising that facial information processing is an important and highly active subfield of cognitive science research. The face is a complex stimulus displaying information about identity, age, gender, as well as emotional and attention state. Here we consider the problem of extracting information about emotional state (facial expression) from single images. Due to the difficulty of obtaining controlled video sequences of standard facial expressions, many psychological and neurophysiologic studies of facial expression processing have used single image motivations. In proposed system, in contrast to the mainstream approaches, we are trying to build a probabilistic model based on the Dynamic Bayesian Network (DBN) to capture the facial interactions at different levels. Hence the proposed system deal with the identification of facial expression on the image captured through camera