NDLI: Traffic Density Estimation with On-line SVM Classifier

Content Provider	IEEE Xplore Digital Library
Author	Wassantachat, T. Zhidong Li Jing Chen Yang Wang Tan, E.
Copyright Year	2009
Abstract	Information on the vehicular traffic density in an intelligent transport system (ITS) is presently obtained mainly through loop detectors (LD), traffic radars and surveillance cameras. However, the difficulties and cost of installing loop detectors and traffic radars tend to be significant. Currently, a more advanced method of circumventing this is to develop a sort of virtual loop detector (VLD) by using video content understanding technology to simulate behavior of a loop detector and to further estimate the traffic flow from a surveillance camera. Such a virtual loop detector that requires supervised training with human intervention for its setup. Difficulties also arise when attempting to obtain a reliable and real-time VLD under different illumination, weather conditions and static shadows. In this paper, we study the effectiveness of texture features in describing the traffic density, and propose a real-time VLD based on on-line SVM classifier and a background modeling technique (OSVM-BG) to estimate the traffic density information probabilistically and automatically. The system uses feedback from background modeling to train and update its SVM kernel to self-adapt to various lighting environments. Experimental results show that the system outperforms an existing algorithm and achieves an average accuracy of 89.43% under various illumination changes, weather conditions and especially changing static shadows in daytime.
Starting Page	13
Ending Page	18
File Size	492331
Page Count	6
File Format	PDF
ISBN	9781424447558
DOI	10.1109/AVSS.2009.43
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-09-02
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	on-line SVM Support vector machines Intelligent vehicles Surveillance Support vector machine classification Radar detection Lighting Detectors Density Estimation Traffic control Cameras intelligent transport system Intelligent systems
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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