Tracking feature extraction based on manifold learning framework

doi:10.1080/0952813X.2010.506286

	Tracking feature extraction based on manifold learning framework
	Qiao, Hong 1; Zhang, Peng 2; Zhang, Bo 2; Zheng, Suiwu 1
刊名	JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
	2011
卷号	23 期号:1 页码:23-38
关键词	visual tracking robotic visual tracking feature extraction
ISSN号	0952-813X
DOI	10.1080/0952813X.2010.506286
英文摘要	Manifold learning is a fast growing area of research recently. The main purpose of manifold learning is to search for intrinsic variables underlying high-dimensional inputs which lie on or are close to a low-dimensional manifold. Different from current theoretical works and applications of manifold learning approaches, in our work manifold learning framework is transferred to tracking feature extraction for the first time. The contributions of this article include three aspects. Firstly, in this article, we focus on tracking feature extraction for dynamic visual tracking on dynamic systems. The feature extracted in this article is based on manifold learning framework and is particular for dynamic tracking purpose. It can be directly applied to system control of dynamic systems. This is different from most traditional tracking features which are used for recognition and detection. Secondly, the proposed tracking feature extraction method has been successfully applied to three different dynamic systems: dynamic robot system, intelligent vehicle system and aircraft visual navigation system. Thirdly, experimental results have proven the validity of the tracking method based on manifold learning framework. Particularly, in the tracking experiments the vision system is dynamic. The tracking method is also compared with the well-known mean-shift tracking method, and tracking results have shown that our method outperforms the latter.
资助项目	Chinese Academy of Sciences ; NNSF of China[60675039] ; NNSF of China[60621001] ; NNSF of China[60725310] ; NNSF of China[90820007] ; 863 Program of China[2006AA04Z217] ; 863 Program of China[2007AA04Z228] ; 973 Program of China[2007CB311002]
WOS研究方向	Computer Science
语种	英语
出版者	TAYLOR & FRANCIS LTD
WOS记录号	WOS:000287493400003
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/12308]
专题	中国科学院数学与系统科学研究院
通讯作者	Qiao, Hong
作者单位	1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Appl Math, AMSS, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Qiao, Hong,Zhang, Peng,Zhang, Bo,et al. Tracking feature extraction based on manifold learning framework[J]. JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE,2011,23(1):23-38.
APA	Qiao, Hong,Zhang, Peng,Zhang, Bo,&Zheng, Suiwu.(2011).Tracking feature extraction based on manifold learning framework.JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE,23(1),23-38.
MLA	Qiao, Hong,et al."Tracking feature extraction based on manifold learning framework".JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE 23.1(2011):23-38.