Parametric models for facial features segmentation

Abstract

In this paper, we are dealing with the problem of facial features segmentation (mouth, eyes and eyebrows). A specific parametric model is defined for each deformable feature, each model being able to take into account all the possible deformations. In order to initialize each model, some characteristic points are extracted on each image to be processed (for example, eyes corners, mouth corners and brows corners). In order to fit the model with the contours to be extracted, a gradient flow (of luminance or chrominance) through the estimated contour is maximized because at each point of the searched contour, the gradient (of luminance or chrominance) is normal. The definition of a model associated to each feature offers the possibility to introduce a regularization constraint. However, the chosen models are flexible enough to produce realistic contours for the mouth, the eyes and the eyebrows. This facial features segmentation is the first step of a set of multi-media applications.