Facial landmark detection system using interest-region model and edge energy function

In this paper, we proposed a new facial landmark-detection system using as edge energy function. The facial landmark-detection system is divided into a learning stage and a detection stage. The learning stage creates an interest-region model, to set up a search region of each landmark, as pre-information necessary for a detection stage and creates a detector for each landmark to detect a landmark in a search region. The detection stage sets up a search region of each landmark in an input image with an interest-region model created in the learning stage. Because a landmark to detect from a system has the characteristics of an edge as both edge of an eye, both edge of a mouth and both edges of eyebrows, we have detected a landmark by applying an edge energy function to the Bayesian discrimination method. We have implemented aforementioned technique by abstracting 800 impassive images from the FERET database and have measured data in which the normalized average error distance is less than 0.1 occupying 98% of the total data.