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Vehicle detection grammars with partial occlusion handling for traffic surveillance

文献类型：期刊论文

作者Tian, Bin1; Tang, Ming2; Wang, Fei-Yue1; Tian,Bin
刊名TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
出版日期2015-07-01
卷号56期号:0页码:80-93
关键词Computer vision Grammar model Occlusion handling Part-based object detection Vehicle detection
通讯作者Tian,Bin
英文摘要Traffic surveillance is an important topic in intelligent transportation systems (ITS). Robust vehicle detection is one challenging problem for complex traffic surveillance. In this paper, we propose an efficient vehicle detection method by designing vehicle detection grammars and handling partial occlusion. The grammar model is implemented by novel detection grammars, including structure, deformation and pairwise SVM grammars. First, the vehicle is divided into its constitute parts, called semantic parts, which can represent the vehicle effectively. To increase the robustness of part detection, the semantic parts are represented by their detection score maps. The semantic parts are further divided into sub-parts automatically. The two-layer division of the vehicle is modeled into a grammar model. Then, the grammar model is trained by a designed training procedure to get ideal grammar parameters, including appearance models and grammar productions. After that, vehicle detection is executed by a designed detection procedure with respect to the grammar model. Finally, the issue of vehicle occlusion is handled by designing and training specific grammars. The strategy adopted by our method is first to divide the vehicle into the semantic parts and sub-parts, then to train the grammar productions for semantic parts and sub-parts by introducing novel pairwise SVM grammars and finally to detect the vehicle by applying the trained grammars. Experiments in practical urban scenarios are carried out for complex traffic surveillance. It can be shown that our method adapts to partial occlusion and various challenging cases. (C) 2015 Elsevier Ltd. All rights reserved.
WOS标题词Science & Technology ; Technology
类目[WOS]Transportation Science & Technology
研究领域[WOS]Transportation
关键词[WOS]TRACKING ; SEGMENTATION ; FEATURES ; CAMERA ; SYSTEM
收录类别SCI
语种英语
WOS记录号WOS:000356733400006
源URL[http://ir.ia.ac.cn/handle/173211/7906]  
专题自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
通讯作者Tian,Bin
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Tian, Bin,Tang, Ming,Wang, Fei-Yue,et al. Vehicle detection grammars with partial occlusion handling for traffic surveillance[J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES,2015,56(0):80-93.
APA Tian, Bin,Tang, Ming,Wang, Fei-Yue,&Tian,Bin.(2015).Vehicle detection grammars with partial occlusion handling for traffic surveillance.TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES,56(0),80-93.
MLA Tian, Bin,et al."Vehicle detection grammars with partial occlusion handling for traffic surveillance".TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 56.0(2015):80-93.

入库方式： OAI收割

来源：自动化研究所

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