A robust multiple cues fusion based Bayesian tracker
文献类型：会议论文
| 作者 | Zhang, Xiaoqin ; Liu, Zhiyong; Qiao, Hong
|
| 出版日期 | 2007 |
| 会议名称 | IEEE International Conference on Robotics and Automation |
| 会议日期 | APR 10-14, 2007 |
| 会议地点 | Rome, ITALY |
| 关键词 | appearance model chamfer distance Bayesian tracker template update |
| 通讯作者 | Qiao, Hong |
| 英文摘要 | This paper presents an efficient and robust tracking algorithm based on multiple cues fusion in the Bayesian framework. This method characterizes the object to be tracked using a MOG (mixture of Gaussians) based appearance model and a chamfer-matching based shape model. A selective updating technique for the models is employed to accommodate for appearance and illumination changes. Meantime, the mean shift algorithm is embedded as the prior information into the Bayesian framework to give a heuristic prediction in the hypotheses generation process, which also alleviates the great computational load suffered by the conventional Bayesian tracker. Experimental results demonstrate that, compared with some existing works, the proposed algorithm has a better adaptability to changes of the object as well as the environments. |
| 会议录 | PROCEEDINGS OF THE 2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION
 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/12819]  |
| 专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_机器人应用与理论组 |
| 作者单位 | Chinese Acad Sci, Inst Automat |
| 推荐引用方式 GB/T 7714 | Zhang, Xiaoqin,Liu, Zhiyong,Qiao, Hong. A robust multiple cues fusion based Bayesian tracker[C]. 见:IEEE International Conference on Robotics and Automation. Rome, ITALY. APR 10-14, 2007. |
入库方式： OAI收割
来源：自动化研究所
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