Real time facial expression recognition with AdaBoost
Yübo Wang, Haizhou Ai, Bo Wu, Chang Huang · Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. · 2004
In this paper, we propose a novel method for facial expression recognition. The facial expression is extracted from human faces by an expression classifier that is learned from boosting Haar feature based look-up-table type weak classifiers. The expression recognition system consists of three modules, face detection, facial feature landmark extraction and facial expression recognition. The implemented system can automatically recognize seven expressions in real time that include anger, disgust, fear, happiness, neutral, sadness and surprise. Experimental results are reported to show its potential applications in human computer interaction.