Luigi Di Stefano DEIS, University of Bologna
Viale Risorgimento 2, 40136 Bologna, Italy
Enrico Viarani DEIS, University of Bologna
Viale Risorgimento 2, 40136 Bologna, Italy e-mail

Topic Area: Artificial Intelligence and Decision Support Systems
Keywords: Applications of Pattern Recognition, Computer Vision, Traffic Monitoring

Extended Abstract
This paper describes the research activity currently going on at DEIS, University of Bologna, on the deployment of computer vision techniques for extraction of traffic information from images. The perspective goal of this activity is the development of a low-cost, vision-based traffic monitoring system capable of measuring fundamental traffic parameters, e.g. queue length at intersections, as well as recovering higher level information such as for example assessment of the traffic situation and congestion detection.
In this framework, one basic problem consists in the development of fast and robust algorithms for vehicle detection and tracking. According with related  work, we have chosen to rely on the extraction of motion from image sequences so as to segment out vehicles with respect to still objects (e.g. road, buildings..). In particular, our approach is based on the Block Matching Algorithm (abbreviated as BMA), which used for motion estimation in the MPEG image compression standard. BMA has been employed for vehicle detection in an application aimed at evaluating turning rates at urban crossroad. Unlike techniques based on spatio-temporal derivatives or background subtraction, BMA provides not only detection of moving points but also motion estimation (i.e. a motion vector is associated with image points). This improves the discrimination power in case of partially occluding vehicles and crowded traffic scenes. In addition, specialised hardware for BMA-based real-time motion estimation is available nowadays.

Get the paper postscript file