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Vision-based analysis of pedestrian traffic data

Kelly, Philip and O'Connor, Noel E. (2008) Vision-based analysis of pedestrian traffic data. In: CBMI 2008 - 6th International Workshop on Content-Based Multimedia Indexing, 18-20 June 2008, London, UK. ISBN 978-1-4244-2043-8

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Abstract

Reducing traffic congestion has become a major issue within urban environments. Traditional approaches, such as increasing road sizes, may prove impossible in certain scenarios, such as city centres, or ineffectual if current predictions of large growth in world traffic volumes hold true. An alternative approach lies with increasing the management efficiency of pre-existing infrastructure and public transport systems through the use of Intelligent Transportation Systems (ITS). In this paper, we focus on the requirement of obtaining robust pedestrian traffic flow data within these areas. We propose the use of a flexible and robust stereo-vision pedestrian detection and tracking approach as a basis for obtaining this information. Given this framework, we propose the use of a pedestrian indexing scheme and a suite of tools, which facilitates the declaration of user-defined pedestrian events or requests for specific statistical traffic flow data. The detection of the required events or the constant flow of statistical information can be incorporated into a variety of ITS solutions for applications in traffic management, public transport systems and urban planning.

Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Uncontrolled Keywords:automated highways; computer vision; road traffic; stereo image processing; traffic engineering computing;
Subjects:Computer Science > Information retrieval
Computer Science > Image processing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Electronic Engineering
Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
Publisher:Institute of Electrical and Electronics Engineers
Official URL:http://dx.doi.org/10.1109/CBMI.2008.4564938
Copyright Information:©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Funders:Science Foundation Ireland, SFI 03/IN.3/I361
ID Code:4715
Deposited On:27 Jul 2009 16:30 by Philip Kelly. Last Modified 04 May 2010 15:30

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