Robust Face Tracking based on Bayesian Probability

摘要：

It is a tough task to robust track face in dynamic complex environments with an active camera. A tracking method based on Bayesian probability is proposed to real-time follow-up track moving face in dynamic complex environments. At first frontal face is detected using the Adaboostface detector based on Haar-like features,and is used to initialize the tracking module. Face color feature representation based on histogram is introduced. Face tracking is realized with the enhanced Camshift algorithm implemented in the color probability density distribution image (CPDDI). To consider and suppress disturbance from background,Bayesian probability is used to produce CPDDI. Experimental results show that the presented method is well suitable for tracking face with arbitrary pose in dynamic complex environments with an active camera. The method is computationally efficient and can run in real-time speed completely.

关键词： Adaboost face detector Camshift CPDDI Bayesian probability

作者: Guishan Xiang

作者单位: School of Information and Electronic Engineering,Zhejiang University of Science & Technology Hangzhou,310023,Zhejiang,China

会议类型: 国际会议

会议名称: 2009 9th International Conference on Electronic Measurement & Instruments(第九届电子测量与仪器国际会议 ICEMI2009)

会议地点: 北京

会议语种:英文

页码: 3113-3116

在线出版日期: 2009-08-16（万方平台首次上网日期，不代表论文的发表时间）