DocumentCode
21171
Title
Hierarchical and Networked Vehicle Surveillance in ITS: A Survey
Author
Bin Tian ; Morris, Brendan Tran ; Ming Tang ; Yuqiang Liu ; Yanjie Yao ; Chao Gou ; Dayong Shen ; Shaohu Tang
Author_Institution
State Key Lab. of Manage. & Control for Complex Syst., Inst. of Autom., Beijing, China
Volume
16
Issue
2
fYear
2015
fDate
Apr-15
Firstpage
557
Lastpage
580
Abstract
Traffic surveillance has become an important topic in intelligent transportation systems (ITSs), which is aimed at monitoring and managing traffic flow. With the progress in computer vision, video-based surveillance systems have made great advances on traffic surveillance in ITSs. However, the performance of most existing surveillance systems is susceptible to challenging complex traffic scenes (e.g., object occlusion, pose variation, and cluttered background). Moreover, existing related research is mainly on a single video sensor node, which is incapable of addressing the surveillance of traffic road networks. Accordingly, we present a review of the literature on the video-based vehicle surveillance systems in ITSs. We analyze the existing challenges in video-based surveillance systems for the vehicle and present a general architecture for video surveillance systems, i.e., the hierarchical and networked vehicle surveillance, to survey the different existing and potential techniques. Then, different methods are reviewed and discussed with respect to each module. Applications and future developments are discussed to provide future needs of ITS services.
Keywords
computer vision; feature extraction; intelligent transportation systems; object detection; object recognition; traffic engineering computing; video signal processing; video surveillance; ITS; computer vision; hierarchical vehicle surveillance; intelligent transportation system; networked vehicle surveillance; traffic road network; traffic scene; traffic surveillance; video-based surveillance system; Cameras; Computer vision; Feature extraction; Image color analysis; Surveillance; Vehicle detection; Vehicles; Behavior understanding; computer vision; networked surveillance system; traffic surveillance; vehicle detection; vehicle tracking;
fLanguage
English
Journal_Title
Intelligent Transportation Systems, IEEE Transactions on
Publisher
ieee
ISSN
1524-9050
Type
jour
DOI
10.1109/TITS.2014.2340701
Filename
6875912
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