Real Time Facial Expression Analysis with Applications to Facial Animation in MPEG-4

摘要

This paper discusses recognition up to intensities of mix of primary facial expressions in real time. The proposed recognition method is compatible with the MPEG-4 high level expression Facial Animation Parameter (FAP). In our method, the whole facial image is considered as a single pattern without any block segmentation. As model features, an expression vector, viz. low global frequency coefficient (DCT) changes relative to neutral facial image of a person is used. These features are robust and good enough to deal with real time processing. To construct a person specific model, apex images of primary facial expression categories are utilized as references. Personal facial expression space (PFES) is constructed by using multidimensional scaling. PFES with its generalization capability maps an unknown input image relative to known reference images. As PFES possesses linear mapping characteristics, MPEG-4 high level expression FAP can be easily calculated by the location of the input face on PFES. Also, temporal variations of facial expressions can be seen on PFES as trajectories. Experimental results are shown to demonstrate the effectiveness of the proposed method.