Vision-Based Occlusion Handling and Vehicle Classification for Traffic Surveillance Systems
Chang, Jianlong1; Wang, Lingfeng2; Meng, Gaofeng2; Xiang, Shiming2; Pan, Chunhong2
2018-06-01
发表期刊IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE
卷号10期号:2页码:80-92
文章类型Article
摘要Due to the factors such as visual occlusion, illumination change and pose variation, it is a challenging task to develop effective and efficient models for vehicle detection and classification in surveillance videos. Although plenty of existing related models have been proposed, many issues still need to be resolved. Typically, vehicle detection and classification methods should be vulnerable in complex environments. Moreover, in spite of many thoughtful attempts on adaptive appearance models to solve the occlusion problem, the corresponding approaches often suffer from high computational costs. This paper aims to address the above mentioned issues. By analyzing closures and convex hulls of vehicles, we propose a simple but effective recursive algorithm to segment vehicles involved in multiple-vehicle occlusions. Specifically, a deep convolutional neural network (CNN) model is constructed to capture high level features of images for classifying vehicles. Furthermore, a new pre-training strategy based on the sparse coding and auto-encoder is developed to pre-train CNNs. After pre-training, the proposed deep model yields a high performance with a limited labeled training samples.
关键词Visual Occlusion Recursive Segmentation Vehicle Classification Deep Convolutional Neural Network
WOS标题词Science & Technology ; Technology
DOI10.1109/MITS.2018.2806619
关键词[WOS]FRAMEWORK ; IMAGES ; VIDEO
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China (NSFC)(91646207 ; Beijing Nature Science Foundation(4162064) ; 61403376 ; 61370039 ; 91338202)
WOS研究方向Engineering ; Transportation
WOS类目Engineering, Electrical & Electronic ; Transportation Science & Technology
WOS记录号WOS:000430717200011
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/20365
专题模式识别国家重点实验室_先进数据分析与学习
作者单位1.Univ Chinese Acad Sci, Sch Comp & Control Engn, Beijing 100049, Peoples R China
2.Chinese Acad Sci, Inst Automat, Dept Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
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GB/T 7714
Chang, Jianlong,Wang, Lingfeng,Meng, Gaofeng,et al. Vision-Based Occlusion Handling and Vehicle Classification for Traffic Surveillance Systems[J]. IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE,2018,10(2):80-92.
APA Chang, Jianlong,Wang, Lingfeng,Meng, Gaofeng,Xiang, Shiming,&Pan, Chunhong.(2018).Vision-Based Occlusion Handling and Vehicle Classification for Traffic Surveillance Systems.IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE,10(2),80-92.
MLA Chang, Jianlong,et al."Vision-Based Occlusion Handling and Vehicle Classification for Traffic Surveillance Systems".IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE 10.2(2018):80-92.
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