Multi-Information Fusion for Scale Selection in Robot Tracking

CORC > 自动化研究所 > 中国科学院自动化研究所 > 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

	Multi-Information Fusion for Scale Selection in Robot Tracking
	Zhang, Xiaoqin; Qiao, Hong; Liu, Zhiyong
	2006
会议名称	IEEE/RSJ International Conference on Intelligent Robots and Systems
会议日期	OCT 09-13, 2006
会议地点	Beijing, PEOPLES R CHINA
关键词	mean shift integral projection kernel bandwidth
通讯作者	Zhang, Xiaoqin)
英文摘要	Mean shift, for its simplicity and efficiency, has achieved a considerable success in robot tracking. For the mean shift based tracking algorithm, the scale of the mean-shift kernel bandwidth is a crucial parameter which reflects the size of tracking window. However, in literature how to properly update or select the bandwidth remains a tough task as the size of the object under consideration changes. In this paper, a weighted average integral projection approach is proposed to extract the local information of the object, and then a multi-information fusion strategy is suggested for the scale selection, which combines both the global and local information of the sample weight image. Moreover, a coarse-to-fine approximate approach is employed to accelerate the procedure. Experimental results demonstrate that, compared to some existing works, the strategy proposed has a better adaptability as the size of the object changes in clutter environments.
会议录	2006 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS
内容类型	会议论文
源URL	[http://ir.ia.ac.cn/handle/173211/12824]
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,Qiao, Hong,Liu, Zhiyong. Multi-Information Fusion for Scale Selection in Robot Tracking[C]. 见:IEEE/RSJ International Conference on Intelligent Robots and Systems. Beijing, PEOPLES R CHINA. OCT 09-13, 2006.