Identification and Recognition of Facial Expressions Using Image Processing Techniques: A Survey

Facial expressions give important information about emotions of a person. Understanding facial expressions accurately is one of the challenging tasks for interpersonal relationships. Automatic emotion detection using facial expressions recognition is now a main area of interest within various fields such as computer science, medicine, and psychology. HCI research communities also use automated facial expression recognition system for better results. Various feature extraction techniques have been developed for recognition of expressions from static images as well as real time videos. The expression recognition model is oriented on the Facial Action Coding System (FACS). The hard constraints on the scene processing and recording conditions set a limited robustness to the analysis. A probabilistic oriented framework is used in order to manage the uncertainties and lack of information. The support for the specific processing involved was given through a Multimodal data fusion platform. The Bayesian network is used to encode the dependencies among the variables. The temporal dependencies are to be extracted to make the system be able to properly select the right expression of emotion. In this way, the system is able to overcome the performance of the previous approaches that dealt only with prototypic facial expression.