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Proceedings Paper

Real-time vision-based traffic flow measurements and incident detection
Author(s): Barak Fishbain; Ianir Ideses; David Mahalel; Leonid Yaroslavsky
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Paper Abstract

Visual surveillance for traffic systems requires short processing time, low processing cost and high reliability. Under those requirements, image processing technologies offer a variety of systems and methods for Intelligence Transportation Systems (ITS) as a platform for traffic Automatic Incident Detection (AID). There exist two classes of AID methods mainly studied: one is based on inductive loops, radars, infrared sonar and microwave detectors and the other is based on video images. The first class of methods suffers from drawbacks in that they are expensive to install and maintain and they are unable to detect slow or stationary vehicles. Video sensors, on the other hand, offer a relatively low installation cost with little traffic disruption during maintenance. Furthermore, they provide wide area monitoring allowing analysis of traffic flows and turning movements, speed measurement, multiple-point vehicle counts, vehicle classification and highway state assessment, based on precise scene motion analysis. This paper suggests the utilization of traffic models for real-time vision-based traffic analysis and automatic incident detection. First, the traffic flow variables, are introduced. Then, it is described how those variables can be measured from traffic video streams in real-time. Having the traffic variables measured, a robust automatic incident detection scheme is suggested. The results presented here, show a great potential for integration of traffic flow models into video based intelligent transportation systems. The system real time performance is achieved by utilizing multi-core technology using standard parallelization algorithms and libraries (OpenMP, IPP).

Paper Details

Date Published: 4 February 2009
PDF: 12 pages
Proc. SPIE 7244, Real-Time Image and Video Processing 2009, 72440I (4 February 2009); doi: 10.1117/12.812976
Show Author Affiliations
Barak Fishbain, Tel-Aviv Univ. (Israel)
Univ. of California, Berkeley (United States)
Ianir Ideses, Tel-Aviv Univ. (Israel)
David Mahalel, Technion - Israel Institute of Technology (Israel)
Leonid Yaroslavsky, Tel-Aviv Univ. (Israel)

Published in SPIE Proceedings Vol. 7244:
Real-Time Image and Video Processing 2009
Nasser Kehtarnavaz; Matthias F. Carlsohn, Editor(s)

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