Detection of abandoned objects in crowded environments

Authors:
Medha Bhargava; Chia-Chih Chen;M. S. Ryoo;J. K. Aggarwal
Affiliations:
Computer and Vision Research Center, Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712, USA;Computer and Vision Research Center, Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712, USA;Computer and Vision Research Center, Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712, USA;Computer and Vision Research Center, Department of Electrical and Computer Engineering, The University of Texas at Austin, 78712, USA
Venue:
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Year:
2007

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Abstract

With concerns about terrorism and global security on the rise, it has become vital to have in place efficient threat detection systems that can detect and recognize potentially dangerous situations, and alert the authorities to take appropriate action. Of particular significance is the case of unattended objects in mass transit areas. This paper describes a general framework that recognizes the event of someone leaving a piece of baggage unattended in forbidden areas. Our approach involves the recognition of four sub-events that characterize the activity of interest. When an unaccompanied bag is detected, the system analyzes its history to determine its most likely owner(s), where the owner is defined as the person who brought the bag into the scene before leaving it unattended. Through subsequent frames, the system keeps a lookout for the owner, whose presence in or disappearance from the scene defines the status of the bag, and decides the appropriate course of action. The system was successfully tested on the i-LIDS dataset.