A robust multiple cues fusion based Bayesian tracker

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 机器人理论与应用

	A robust multiple cues fusion based Bayesian tracker
	Zhang, Xiaoqin; Liu, Zhiyong; Qiao, Hong
	2007
会议名称	IEEE International Conference on Robotics and Automation
会议录名称	PROCEEDINGS OF THE 2007 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION
会议日期	APR 10-14, 2007
会议地点	Rome, ITALY
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.
关键词	Appearance Model Chamfer Distance Bayesian Tracker Template Update
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/12819
专题	多模态人工智能系统全国重点实验室_机器人理论与应用
通讯作者	Qiao, Hong
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],2007.