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Real-time vandalism detection by monitoring object activities

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Abstract

This paper proposes a novel method for the detection of vandalism events in video sequences. The method is based on a proposed definition for common vandal behaviors recorded on surveillance video sequences. To do this, the method monitors changes inside a restricted site containing vandalism-prone objects such as a vending machine, a pay phone, or a street sign. When an object is detected as leaving such a site, the proposed method checks if the site contains temporally consistent and significant static changes, representing damage. If there are such changes and given that the site is normally unchanged after legal use, a vandalism event is declared and the vandals are tracked. The proposed method is tested on video sequences showing real and simulated vandal behaviors and it achieves a detection rate of 96%. It detects different forms of vandalism such as graffiti and theft, and can handle sudden illumination changes, occlusions, and segmentation errors. The proposed method operates at a frame rate of 13 frames per second.

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Authors and Affiliations

  1. Electrical and Computer Engineering, Concordia University, 1455 de Maisonneuve, West Montréal, QC, H3G 1M8, Canada

    Mohammed Ghazal & Aishy Amer

  2. Communications Research Centre Canada, P.O. Box 11490, Stn. H, 3701 Carling Ave., Ottawa, ON, K2H 8S2, Canada

    Carlos Vázquez

Authors
  1. Mohammed Ghazal
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  2. Carlos Vázquez
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  3. Aishy Amer
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Corresponding author

Correspondence to Mohammed Ghazal.

Additional information

This work was supported, in part, by the Natural Sciences and Engineering Research Council (NSERC) of Canada.

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Ghazal, M., Vázquez, C. & Amer, A. Real-time vandalism detection by monitoring object activities. Multimed Tools Appl 58, 585–611 (2012). https://doi.org/10.1007/s11042-011-0751-z

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