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
Link To Document :
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