Face tracking using a region-based mean-shift algorithm with adaptive object and background models

This paper proposes a technique for face tracking based on the mean shift algorithm and the segmentation of the images into regions homogeneous in color. Object and background are explicitly modeled and updated through the tracking process. Color and shape information are used to define with precision the face contours, providing a mechanism to adapt the tracker to variations in object scale and to illumination and background changes.