Institutions | About Us | Help | Gaeilge
rian logo


Mark
Go Back
Vision-based analysis of pedestrian traffic data
Kelly, Philip; O'Connor, Noel E.
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.
Keyword(s): Information retrieval; Image processing; automated highways; computer vision; road traffic; stereo image processing; traffic engineering computing
Publication Date:
2008
Type: Other
Peer-Reviewed: Unknown
Language(s): English
Institution: Dublin City University
Citation(s): Kelly, Philip and O'Connor, Noel E. ORCID: 0000-0002-4033-9135 <https://orcid.org/0000-0002-4033-9135> (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
Publisher(s): Institute of Electrical and Electronics Engineers
File Format(s): application/pdf
Related Link(s): http://doras.dcu.ie/4715/1/cbmi.pdf,
http://dx.doi.org/10.1109/CBMI.2008.4564938
First Indexed: 2009-11-05 02:01:38 Last Updated: 2019-02-09 06:58:24