Face tracking with occlusion

摘要：

The Camshift algorithm falls to track face easily while it is occluded, so a new face tracking method is proposed in this paper. This method combines the Camshift algorithm and the GM(1,1) model with optimized background values. By using moving vector information, this method can effectively track face even occluded by other static objects. The GM(1,1) prediction model will reduce the searching region of the Camshift algorithm and enhance real-time performance. Furthermore this model is not only suitable for modeling of low increase exponential sequence but also suitable for high increase exponential sequence, so it adapts to the characteristic of humans free motion. With occlusion, this method can improve accuracy of human face tracking and enhance robustness of the tracking algorithm by replacing the real values with the prediction values containing prediction errors.

关键词： Camshifl GM(1,1) model face tracking occlusion

作者: Jianxiong Tang Jianxin Zhang

作者单位: Zhejiang Institute of Communications,Hangzhou 311112,China Zhejiang Sci-Tech University,Hangzhou 310018,China

会议类型: 国际会议

会议名称: 2009 International Conference on Measuring Technology and Mechatronics Automation(ICMTMA 2009)(2009年检测技术与机械自动化国际会议)

会议地点: 长沙

会议语种:英文

页码: 465-468

在线出版日期: 2009-04-11（万方平台首次上网日期，不代表论文的发表时间）