KMS Of Academy of mathematics and systems sciences, CAS
| Tracking feature extraction based on manifold learning framework | |
Qiao, Hong1; Zhang, Peng2; Zhang, Bo2 ; Zheng, Suiwu1
| |
| 2011 | |
| Source Publication | JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
 |
| ISSN | 0952-813X |
| Volume | 23Issue:1Pages:23-38 |
| Abstract | 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. |
| Keyword | visual tracking robotic visual tracking feature extraction |
| DOI | 10.1080/0952813X.2010.506286 |
| Language | 英语 |
| Funding Project | 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 Research Area | Computer Science |
| WOS Subject | Computer Science, Artificial Intelligence |
| WOS ID | WOS:000287493400003 |
| Publisher | TAYLOR & FRANCIS LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/12309 |
| Collection | 应用数学研究所 |
| Corresponding Author | Qiao, Hong |
| Affiliation | 1.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 2.Chinese Acad Sci, Inst Appl Math, AMSS, Beijing 100190, Peoples R China |
| Recommended Citation 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. |
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