Computer vision techniques for traffic flow computation

Authors:
Li Bai;William Tompkinson;Yan Wang
Affiliations:
School of Computer Science and Information Technology, University of Nottingham, Jubilee Campus, Wollaton Road, NG8 1BB, Nottingham, UK;Ordnance Survey, Research and Innovation, Romsey Road, SO16 4GU, Southampton, UK;School of Computer Science and Information Technology, University of Nottingham, Jubilee Campus, Wollaton Road, NG8 1BB, Nottingham, UK
Venue:
Pattern Analysis & Applications
Year:
2004

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Abstract

This paper describes an application of computer vision techniques to road surveillance. It reports on a project undertaken in collaboration with the Research and Innovation group at the Ordnance Survey. The project aims to produce a system that detects and tracks vehicles in real traffic scenes to generate meaningful parameters for use in traffic management. The system has now been implemented using two different approaches: a feature-based approach that detects and groups corner features in a scene into potential vehicle objects, and an appearance-based approach that trains a cascade of classifiers to learn the appearances of vehicles as an arrangement of a set of pre-defined simple Haar features. Potential vehicles detected are then tracked through an image sequence, using the Kalman filter motion tracker. Experimental results of the algorithms are presented in this paper.