A New Face Tracking Algorithm Based on Local Binary Pattern and Skin Color Information

Abstract

A new algorithm for face tracking is proposed. Color information provides an effective cue for face tracking due to its robustness to scaling, rotation and translation. But the main limitation of color cue is that it can be easily interrupted by the camouflage objects that have the same or similar color with the target face. In order to achieve robust face tracking performance, the texture feature is used for face description, which describes the detailed information of the face. The LBP (Local Binary Pattern) is a new way to extract the texture feature. Particle filter is a successful and powerful estimation method. This paper fuses the color cue and LBP cue under the framework of particle filter. The tracking results show a more robust face tracking performance compared with the method based on single cue.