Facial-expression data often appear in multiple views either due to head-movements or the camera position. Existing methods for multi-view facial expression recognition perform classification of the target expressions either by using classifiers learned separately for each view or by using a single classifier learned for all views. However, these approaches do not explore the fact that multi-vi...

Human Machine Interaction systems are able to perceive facial expressions more naturally and reliably. In this paper, we introduced a new idea to recognize facial expression by selecting the most discriminative facial regions relying on facial expression appearance. The proposed approach is based on the prior knowledge of psychology studies which show that only some facial regions are descripti...

----------------------------------------------------------------***-----------------------------------------------------------------Abstract The automatic Facial Expression Recognition has been one of the latest research topic since 1990's. Face Expression plays an important role in human communication. This paper presents a high-level overview of automatic expression recognition; it highlights...

In this paper, we propose an interactive system for reconstructing human facial expression. In the system, a nonlinear mass-spring model is employed to simulate twenty two facial muscles’ tensions during facial expressions, and then the elastic forces of these tensions are grouped into a vector which is used as the input for facial expression recognition. The experimental results show that the ...

In this paper, we present a method to generate dynamic textures for facial expression. We first build a facial texture library for a head model. This series of facial textures correspond to each facial expression. For each facial expression we calculate the expression parameters and store it in the library. We use the expression parameter to transfer an expressive texture from one character to ...