Recognition of six basic facial expressions by feature-points tracking using RBF neural network and fuzzy inference system
Hadi Seyedarabi, Ali Aghagolzadeh, Sohrab Khanmohammadi · 2005
Face expression recognition is useful for designing new interactive devices offering the possibility of new ways for human to interact with computer systems. In this paper, we develop a facial expression recognition system, based on the facial features extracted from facial characteristic points in frontal image sequences. Selected facial feature points were automatically tracked using a cross-correlation based optical flow, and extracted feature vectors were used to classify expressions, using RBF neural networks and a fuzzy inference system (FIS). Then, recognition results from two classifiers were compared with each other. Success rates were about 91.6% using RBF and 89.1% using FIS classifiers