Open Access

Robust Vehicle and Traffic Information Extraction for Highway Surveillance

EURASIP Journal on Advances in Signal Processing20052005:912501

https://doi.org/10.1155/ASP.2005.2305

Received: 1 January 2004

Published: 25 August 2005

Abstract

A robust vision-based traffic monitoring system for vehicle and traffic information extraction is developed in this research. It is challenging to maintain detection robustness at all time for a highway surveillance system. There are three major problems in detecting and tracking a vehicle: (1) the moving cast shadow effect, (2) the occlusion effect, and (3) nighttime detection. For moving cast shadow elimination, a 2D joint vehicle-shadow model is employed. For occlusion detection, a multiple-camera system is used to detect occlusion so as to extract the exact location of each vehicle. For vehicle nighttime detection, a rear-view monitoring technique is proposed to maintain tracking and detection accuracy. Furthermore, we propose a method to improve the accuracy of background extraction, which usually serves as the first step in any vehicle detection processing. Experimental results are given to demonstrate that the proposed techniques are effective and efficient for vision-based highway surveillance.

Keywords

traffic monitoring object tracking moving cast shadow occlusion nighttime detection background subtraction

Authors’ Affiliations

(1)
Multimedia Communications Lab., KDDI R&D Laboratories Inc.
(2)
Department of Electrical Engineering and Integrated Media Systems Center, USC Viterbi School of Engineering, University of Southern California

Copyright

© Yoneyama et al. 2005