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Pedestrian Counting With Back-Propagated Information and Target Drift Remedy
Chen, Ke1; Zhang, Zhaoxiang2; Zhaoxiang Zhang
2017-04-01
发表期刊IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
卷号47期号:4页码:639-647
文章类型Article
摘要Pedestrian density is one of the important factors in designing visual surveillance and intelligent transportation systems, but it is challenging to obtain accurate and robust estimates because of both inconsistent crowd patterns in the scenes and target drift caused by imbalanced data distribution. Most of existing global regression frameworks focus on the former challenge to improve the robustness of regression learning, but very few work concerns on mitigating the suffering from the latter one. This paper proposes a novel counting-by-regression framework to utilize the importance of training samples to improve the robustness against inconsistent feature-target relationship based on a recently-proposed learning paradigm-learning with privileged information. To this end, the concept of back-propagation is for the first time considered to select more informative samples contributed to robust fitting performance. Moreover, the direction of target drift along the continuously-changing target dimension is discovered by learning local classifiers under different situation of pedestrian density, which can thus be exploited in our algorithm to further boost the performance. Experimental evaluation on the public UCSD and shopping Mall benchmarks verifies that our approach significantly beats the state-of-the-art counting-by-regression frameworks.
关键词Back-propagated Cumulative Attributes Pedestrian Counting Regression Learning Visual Surveillance
WOS标题词Science & Technology ; Technology
DOI10.1109/TSMC.2016.2618916
关键词[WOS]AGE ESTIMATION ; CROWD DENSITY ; CLASSIFICATION ; REGRESSION ; PEOPLE
收录类别SCI
语种英语
项目资助者Academy of Finland(267581 ; National Natural Science Foundation of China(61375036 ; 298700) ; 61511130079)
WOS研究方向Automation & Control Systems ; Computer Science
WOS类目Automation & Control Systems ; Computer Science, Cybernetics
WOS记录号WOS:000398966700006
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/14034
专题类脑智能研究中心
通讯作者Zhaoxiang Zhang
作者单位1.Tampere Univ Technol, Dept Signal Proc, FIN-33101 Tampere, Finland
2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Inst Automat, Beijing 100190, Peoples R China
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Chen, Ke,Zhang, Zhaoxiang,Zhaoxiang Zhang. Pedestrian Counting With Back-Propagated Information and Target Drift Remedy[J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,2017,47(4):639-647.
APA Chen, Ke,Zhang, Zhaoxiang,&Zhaoxiang Zhang.(2017).Pedestrian Counting With Back-Propagated Information and Target Drift Remedy.IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS,47(4),639-647.
MLA Chen, Ke,et al."Pedestrian Counting With Back-Propagated Information and Target Drift Remedy".IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 47.4(2017):639-647.
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