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

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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.

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Acknowledgments

We would like to thank Transport Canada (Transport Canada has provided co-funding to this project, through Canada’s Strategic Highway Infrastructure Program), Alberta Infrastructure and Transportation, The City of Calgary, The University of Calgary, Schulich School of Engineering, and Department of Electrical and Computer Engineering, for their financial and technical support they are providing to us during the period of this research project.

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Authors and Affiliations

  1. Intellivie Technologies Inc., #5, 3535 Research Road, N.W., Calgary, Alberta, T2L 2K8, Canada

    Jun Cai & Wael Badawy

  2. Department of Electrical Engineering, Faculty of Engineering, Benha University, 108 Shoubra Street, Cairo, Egypt

    Mohamed Shehata

  3. Department of Electrical and Computer Engineering, University of Calgary, 2500 University Drive, N.W., Calgary, Alberta, T2N 1N4, Canada

    Wael Badawy

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  1. Jun Cai
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  2. Mohamed Shehata
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  3. Wael Badawy
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Correspondence to Mohamed Shehata.

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Cai, J., Shehata, M. & Badawy, W. A Robust Video-Based Algorithm for Detecting Snow Movement in Traffic Scenes. J Sign Process Syst Sign Image Video Technol 56, 307–326 (2009). https://doi.org/10.1007/s11265-008-0241-3

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  • DOI: https://doi.org/10.1007/s11265-008-0241-3

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