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Detection of object abandonment using temporal logic

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Abstract

This paper describes a novel framework for a smart threat detection system that uses computer vision to capture, exploit and interpret the temporal flow of events related to the abandonment of an object. Our approach uses contextual information along with an analysis of the causal progression of events to decide whether or not an alarm should be raised. When an unattended object is detected, the system traces it back in time to determine and record who its most likely owner(s) may be. Through subsequent frames, the system searches the scene for the owner and issues an alert if no match is found for the owner over a given period of time. Our algorithm has been successfully tested on two benchmark datasets (PETS 2006 Benchmark Data, 2006; i-LIDS Dataset for AVSS, 2007), and yielded results that are substantially more accurate than similar systems developed by other academic and industrial research groups.

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Author notes

  1. Medha Bhargava

    Present address: CGGVeritas, Brentford, UK

Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Computer and Vision Research Center, The University of Texas at Austin, Austin, TX, 78712-0240, USA

    Medha Bhargava, Chia-Chih Chen, M. S. Ryoo & J. K. Aggarwal

Authors
  1. Medha Bhargava
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  2. Chia-Chih Chen
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  3. M. S. Ryoo
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  4. J. K. Aggarwal
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Corresponding author

Correspondence to Chia-Chih Chen.

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Bhargava, M., Chen, CC., Ryoo, M.S. et al. Detection of object abandonment using temporal logic. Machine Vision and Applications 20, 271–281 (2009). https://doi.org/10.1007/s00138-008-0181-8

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  • DOI: https://doi.org/10.1007/s00138-008-0181-8

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