LAFTER: a real-time face and lips tracker with facial expression recognition

摘要

This paper describes an active-camera real-time system for tracking, shape description, and classification of the human face and mouth expressions using only a PC or equivalent computer. The system is based on use of 2-D blob features, which are spatially compact clusters of pixels that are similar in terms of low-level image properties. Patterns of behavior (e.g., facial expressions and head movements) can be classified in real-time using hidden Markov models (HMMs). The system has been tested on hundreds of users and has demonstrated extremely reliable and accurate performance. Typical facial expression classification accuracies are near 100%.