KMS Of Academy of mathematics and systems sciences, CAS
A New Algorithm for Robust Pedestrian Tracking Based on Manifold Learning and Feature Selection | |
Wang, Min1; Qiao, Hong1; Zhang, Bo2,3 | |
2011-12-01 | |
发表期刊 | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS |
ISSN | 1524-9050 |
卷号 | 12期号:4页码:1195-1208 |
摘要 | Manifold learning has been a popular method in many areas such as classification and recognition. In this paper, we propose a novel algorithm for pedestrian tracking based on our previous work on manifold learning. A new kind of manifold subspace is introduced, in which the intrinsic features of the target's motion can be best preserved, and the dimensionality of feature is very low. In the proposed subspace, variations of continuous pedestrian postures can be represented well by these intrinsic features. This also validates our conjecture that the movement of pedestrians can be described by some intrinsic and low-dimensional features, which are significant for tracking. Although intrinsic features are useful for tracking, algorithms that directly apply intrinsic features could not guarantee stable performance due to the influence from a complicated background. To address this issue, a foreground extraction method is introduced to enhance tracking stability by selecting the most discriminative color features to automatically distinguish the foreground from the candidate image. This preprocessing stage is proven to promote the accuracy of low-dimensional feature representation in pedestrian tracking. The whole tracking procedure, particularly dimensionality reduction, is linear and fast without complicated calculations. The experimental results validate the effectiveness of our algorithm under challenging conditions, such as a complex background, various pedestrian postures, and even occlusion. |
关键词 | Feature extraction manifold learning tracking |
DOI | 10.1109/TITS.2011.2148717 |
语种 | 英语 |
资助项目 | National Natural Science Foundation (NNSF) of China[61033011] ; National Natural Science Foundation (NNSF) of China[60725310] ; National Natural Science Foundation (NNSF) of China[90820007] ; 863 Program of China[2007AA04Z228] ; 973 Program of China[2007CB311002] |
WOS研究方向 | Engineering ; Transportation |
WOS类目 | Engineering, Civil ; Engineering, Electrical & Electronic ; Transportation Science & Technology |
WOS记录号 | WOS:000297588500025 |
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/12417 |
专题 | 应用数学研究所 |
通讯作者 | Wang, Min |
作者单位 | 1.Chinese Acad Sci, Lab Complex Syst & Intelligent Sci, Inst Automat, Beijing 100190, Peoples R China 2.Chinese Acad Sci, State Key Lab Sci & Engn Comp, Acad Math & Syst Sci, Beijing 100190, Peoples R China 3.Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Min,Qiao, Hong,Zhang, Bo. A New Algorithm for Robust Pedestrian Tracking Based on Manifold Learning and Feature Selection[J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,2011,12(4):1195-1208. |
APA | Wang, Min,Qiao, Hong,&Zhang, Bo.(2011).A New Algorithm for Robust Pedestrian Tracking Based on Manifold Learning and Feature Selection.IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS,12(4),1195-1208. |
MLA | Wang, Min,et al."A New Algorithm for Robust Pedestrian Tracking Based on Manifold Learning and Feature Selection".IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 12.4(2011):1195-1208. |
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