Adaptive unscented Kalman filters applied to visual tracking

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	Adaptive unscented Kalman filters applied to visual tracking
	Ding QC(丁其川); Zhao XG(赵新刚); Han JD(韩建达)
	2012
会议名称	2012 IEEE International Conference on Information and Automation, ICIA 2012
会议日期	June 6, 2012 - June 8, 2012
会议地点	Shenyang, China
关键词	Estimation Nonlinear filtering Tracking (position)
页码	491-496
通讯作者	丁其川
中文摘要	The classic Bays filters applied to model-based visual tracking suffers from high computation complexity and performance degradation when the inaccurate priori knowledge is involved. In order to improve tracking real-time and accuracy, two kinds of adaptive unscented Kalman filters (AUKFs), named the MIT-based AUKF and the master-slave-structure AUKF, respectively, are proposed to estimate the 3-D rigid-body motion from sequential images. The filters use certain feature points' image coordinates as input data to estimate the position and orientation of the object at each instant when an image is captured, and to recover the velocity and angular velocity of the object between consecutive frames. Experimental results show that both the AUKFs can improve estimation real-time and accuracy in visual tracking. © 2012 IEEE.
收录类别	EI ; CPCI（ISTP）
产权排序	1
会议录	2012 IEEE International Conference on Information and Automation, ICIA 2012
会议录出版者	IEEE Computer Society
会议录出版地	Washington, DC
语种	英语
ISBN号	978-1-4673-2238-6
WOS记录号	WOS:000318899300088
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/9864]
专题	沈阳自动化研究所_机器人学研究室
推荐引用方式 GB/T 7714	Ding QC,Zhao XG,Han JD. Adaptive unscented Kalman filters applied to visual tracking[C]. 见:2012 IEEE International Conference on Information and Automation, ICIA 2012. Shenyang, China. June 6, 2012 - June 8, 2012.