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Region-Based Trajectory Analysis for Abnormal Behaviour Detection: A Trial Study for Suicide Detection and Prevention

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Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges (ICPR 2022)

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Abstract

We propose a region-based trajectory analysis method to detect abnormal activities in a scene. It provides a self-adapted, location-sensitive and interpretable trajectory analysis method for different scenarios. Our integrated pipeline consists of a pedestrian detection and tracking module to extract density, speed and direction features. In addition, it contains a grid-based feature extraction and clustering module that automatically generates a region map with corresponding feature importance. During testing, the pipeline analyses the segments that fall into the regions, but do not comply with the important features, and clusters trajectories together to detect abnormal behaviours. Our case study of a suicide hotspot proves the effectiveness of such an approach.

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Acknowledgment

The authors would like to thank Woollahra Municipal Council for sharing information on the use of CCTV as part of their commitment to self-harm minimization within their local area and the work they are doing with police and emergency response personnel and mental health support agencies. This work was supported by a Suicide Prevention Research Fund Innovation Grant, managed by Suicide Prevention Australia, and the NHMRC Centre of Research Excellence in Suicide Prevention (APP1152952). The contents of this manuscript are the responsibility of the authors, and have not been approved or endorsed by the funders.

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Authors and Affiliations

  1. School of Computer Science and Engineering, University of New South Wales, Sydney, NSW, 2052, Australia

    Xun Li, Ryan Anthony de Belen & Arcot Sowmya

  2. Black Dog Institute, University of New South Wales, Sydney, NSW, 2031, Australia

    Sandersan Onie & Mark Larsen

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  1. Xun Li
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  2. Ryan Anthony de Belen
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  3. Arcot Sowmya
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  4. Sandersan Onie
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  5. Mark Larsen
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Corresponding author

Correspondence to Ryan Anthony de Belen .

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Editors and Affiliations

  1. York University, Toronto, ON, Canada

    Jean-Jacques Rousseau

  2. Ontario Tech University, Oshawa, ON, Canada

    Bill Kapralos

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Li, X., de Belen, R.A., Sowmya, A., Onie, S., Larsen, M. (2023). Region-Based Trajectory Analysis for Abnormal Behaviour Detection: A Trial Study for Suicide Detection and Prevention. In: Rousseau, JJ., Kapralos, B. (eds) Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges. ICPR 2022. Lecture Notes in Computer Science, vol 13643. Springer, Cham. https://doi.org/10.1007/978-3-031-37660-3_13

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  • DOI: https://doi.org/10.1007/978-3-031-37660-3_13

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