An Efficient Approach – Patterns of Oriented Motion Flow based Facial Expression Recognition from Depth Video
The detection of facial expressions from images or videos have become very prominent in the field of computer vision. Human facial expressions are result of three major components. First component can be defined as facial feature points around each facial component. These facial components can be eyebrows, mouth, etc. These facial components help us to collect face shape knowledge. Second component can be considered as the facial muscle movement which result in contraction or relaxation of the facial components which result in expression. For example, eyelid tightener, eyebrow raiser, etc. The final component is the actual human expression caused by movement of global facial muscles which define human emotion states. This paper proposes an efficient approach for expression recognition. This paper defines a pattern-oriented motion flow methodology towards which detects expression based on frame to frame expression change.
Keywords: POMF – Pattern Oriented Motion Flow, Facial Expression, Facial Features, Computer Vision.