Facial Emotion Feature Extraction Based Eigenface for 3D Video

Abstract

Recent psychological research has shown that facial expressions are the most expressive way in which humans display emotion. Facial expressions are widely used in the behavioral interpretation of emotions, cognitive science, and social interactions. Therefore, automated and real-time facial expression recognition would be useful in many applications, such as human computer interfaces, virtual reality, video-conferencing, customer satisfaction studies, etc. This paper presents a proposed technique for facial expression extraction, which based on the Appearance Features Technique - Principle Component Analysis (PCA), which depending on extract features (largest Eigenvalues and Eigenvectors).

Experimental results show the quick technique for feature extraction of 3D video frames, which takes 5.1 seconds in the process of feature extraction.