Particle Filter Face Tracking Using Color and Shape Histogram as Clues
以颜色和形状直方图为线索的粒子滤波人脸跟踪

Face tracking problem comprises two key factors: one is the design of tracker;the other is the selection and representation of tracking cues.To relieve the shortcoming that the general face tracer is frequently disturbed by background when a simple ellipse model is used to describe the facial shape,and in accordance with the fact that the dynamic model and observation model of video object tracking problem are always non-Gaussian and non-linear,a robust particle filter face tracking algorithm which uses shape and color represented in the form of histogram as clues is proposed.The tracking algorithm is based on particle filter,in which a new shape representation method using histogram is introduced and modified to be as one of tracking clues.At the same time,an experiential edge detection algorithm is proposed in order to alleviate background disturbance.Experimental results show that the proposed algorithm is robust to the rotation of face,background skin color distraction and partial occlusion.In addition,the proposed tracker can recover the lost terget due to the severe occlusion.