Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking

doi:10.1109/TSMCB.2009.2031559

CSpace > 应用数学研究所

	Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking
	Qiao, Hong 1; Zhang, Peng 2,3; Zhang, Bo3 ; Zheng, Suiwu
	2010-06-01
发表期刊	IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
ISSN	1083-4419
卷号	40 期号:3 页码:868-880
摘要	Manifold learning is a hot topic in the field of computer science, particularly since nonlinear dimensionality reduction based on manifold learning was proposed in Science in 2000. The work has achieved great success. The main purpose of current manifold-learning approaches is to search for independent intrinsic variables underlying high dimensional inputs which lie on a low dimensional manifold. In this paper, a new manifold is built up in the training step of the process, on which the input training samples are set to be close to each other if the values of their intrinsic variables are close to each other. Then, the process of dimensionality reduction is transformed into a procedure of preserving the continuity of the intrinsic variables. By utilizing the new manifold, the dynamic tracking of a human who can move and rotate freely is achieved. From the theoretical point of view, it is the first approach to transfer the manifold-learning framework to dynamic tracking. From the application point of view, a new and low dimensional feature for visual tracking is obtained and successfully applied to the real-time tracking of a free-moving object from a dynamic vision system. Experimental results from a dynamic tracking system which is mounted on a dynamic robot validate the effectiveness of the new algorithm.
关键词	Feature extraction robotic visual tracking visual tracking
DOI	10.1109/TSMCB.2009.2031559
语种	英语
资助项目	Chinese Academy of Sciences ; National Natural Science Foundation (NNSF) of China[60675039] ; National Natural Science Foundation (NNSF) of China[60621001] ; 863 Program of China[2006AA04Z217] ; 863 Program of China[2007AA04Z228] ; NNSF of China[60725310] ; NNSF of China[90820007] ; 973 Program of China[2007CB311002]
WOS研究方向	Automation & Control Systems ; Computer Science
WOS类目	Automation & Control Systems ; Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000277774700028
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/11063
专题	应用数学研究所
通讯作者	Qiao, Hong
作者单位	1.Chinese Acad Sci, Lab Complex Syst & Intelligent Sci, Inst Automat, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Grad Sch, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing 100190, Peoples R China 4.Chinese Acad Sci, State Key Lab Sci & Engn Comp, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Qiao, Hong,Zhang, Peng,Zhang, Bo,et al. Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking[J]. IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,2010,40(3):868-880.
APA	Qiao, Hong,Zhang, Peng,Zhang, Bo,&Zheng, Suiwu.(2010).Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking.IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS,40(3),868-880.
MLA	Qiao, Hong,et al."Learning an Intrinsic-Variable Preserving Manifold for Dynamic Visual Tracking".IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 40.3(2010):868-880.