A Robust Video-Based Algorithm for Detecting Snow Movement in Traffic Scenes

Authors:
Jun Cai;Mohamed Shehata;Wael Badawy
Affiliations:
Intellivie Technologies Inc., Calgary, Canada T2L 2K8;Department of Electrical Engineering, Faculty of Engineering, Benha University, Cairo, Egypt;Intellivie Technologies Inc., Calgary, Canada T2L 2K8 and Department of Electrical and Computer Engineering, University of Calgary, Calgary, Canada T2N 1N4
Venue:
Journal of Signal Processing Systems
Year:
2009

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Abstract

Video-based Automatic Incident Detection (AID) systems are widely deployed in many cities for detecting traffic incidents to provide smoother, safer and congestion free traffic flow. However, the accuracy of an AID system operating in an outdoor environment suffers from high false alarm rates due to environmental factors. These factors include snow movement, static shadow and static glare on the roads. In this paper, a robust real-time algorithm is proposed to detect snow movement in video streams to improve the rate of detection. This is done by having the AID system reducing its sensitivity in the areas that have snow movements. The feasibility of the proposed algorithm has been evaluated using traffic videos captured from several cameras at the City of Calgary.