Camera-based vehicle detection and classification

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Traffic congestion in big urban centers cost billions of dollars yearly to commuters. It also adversely affects the health and quality-of-life of commuters. Given current population trends, it seems that traffic congestion will only worsen over time unless drastic measures are taken to curb traffic growth. One low-cost strategy that cities and municipalities are exploring for dealing with burgeoning traffic is the use of intelligent traffic phasing systems. These systems route traffic through road networks while minimizing travel times, reducing stops and saving fuel costs. Standard Power Corporation is a Canadian supplier/consultant/OEM of intelligent traffic detection hardware and systems. They provide road traffic data gathering equipment to a number of municipalities across Canada. In this project, Dr. Qureshi's Visual Computing Lab at the University of Ontario Institute of Technology will work with Standard Power Corporation to develop a camera-based vehicle detection and classification system. The system will use traffic cameras mounted on road intersections to classify vehicles present at the scene. The developed system will provide a rich source for data for subsequent traffic monitoring and analysis, including improved ways to control traffic intersections to ease traffic congestion.