Emotion Recognition by Modeling the Movement
Halima MHAMDI, Nessrine HAMROUNI, Mohamed Salim BOUHLEL
Journal of Information Organization, Vol. 3, No. 2, 2013.
DOI: 
Link: http://www.dline.info/jio/fulltext/v3n2/4.pdf
Abstract:
We are trying, through this paper, to expose emotion recognition approaches. In fact, the facial expressions analysis in computer vision is complicated by the variety of faces from one person to another, as well as problems related to the recording, such as lighting, the position of the face relative to the camera, and occlusions. In the context of the dynamic approaches, we can distinguish two different directions of research: the holistic approaches, where we analyze the face in its entirety, and the local approaches, where we concentrate on facial characteristics representing facial expressions. The relevant characteristic points are in particular eyes, eyebrows, mouth, and possibly the front. In general, the holistic methods are better to determine the expressions in their set, whereas the local methods can detect more subtle changes. Among the various dynamic methods, we find dense Optical flow, applied holistically. This method has also been applied locally by estimating the activity of several facial muscles. The calculation is performed in each window around the selected region of interest.