A 3D geometric approach to face detection and facial expression recognition

Face detection and facial expression recognition are research areas with important application possibilities. Although the two problems are usually dealt with different approaches, we show in this paper how the same recognition process can be used to recognize both a generic “class-face” in a given, possibly complex image, and a specific facial expression. The approach we propose is based on two steps. In the former we use alignment techniques in order to overlap the 3D representations of the main face components with the 2D image elements. In the latter we compare the candidate groups of localized components with a set of structural models, each of which representing a facial expression. Expressionindependent face detection is achieved using the same approach with a model built generalizing over a set of face examples with different expressions.