A Robust Face Tracking Method by Employing Color-based Particle Filter

Human or face tracking in a diverse environment is very important for various applications in computer vision, especially for video surveillance. Usually, a color cue offers many advantages over motion or geometric information which cannot robustly handle partial occlusion, rotation, scale and resolution changes. In this paper, we present a robust face tracking system by employing a color-based particle filter. The face detection technique is realized based on a Haar-like features algorithm. Here we exploit skin color cues for face-tracking, and it also proposes a body-part particle distribution system. This system is robust against occlusion by human or others and it can perform the tracking in real-time. We conducted experiments in both indoor and outdoor environments, with either a single or multiple persons in a view. Based on the color-based and body-part particle filter, we tracked a person’s face satisfactorily by a developed simple robot system.