Facial tracking method with a semi-automatic or automatic facial model initialization process based on Candide3 model

The work focus on the problem of tracking faces and facial actions based on Candide3 facial model. The main contribution of this paper is described as follows. First, a semi-automatic method is developed to initialize face model parameters. Second, an example-based learning method is utilized based on preliminary sample generating work using the semi-automatic method. Third, in order to restrain the effect of illumination, a normalization method is applied. Through the simulation experiments, a conclusion can be summarized that the method in this paper is more convenient and accurate.