Robust abandoned object detection integrating wide area visual surveillance and social context.

Ferryman, James, Hogg, David, Sochman, Jan, Behera, Ardhendu, Rodriguez-Serrano, Jose, Worgan, Simon, Li, Longzhen, Leung, Valerie, Evans, Murray, Cornic, Philippe, Herbin, Stephane, Schlenger, Stefan and Dose, Michael (2013) Robust abandoned object detection integrating wide area visual surveillance and social context. Pattern Recognition Letters, 34 (7). pp. 789-798. DOI https://doi.org/10.1016/j.patrec.2013.01.018

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Abstract

This paper presents a video surveillance framework that robustly and efficiently detects abandoned objects in surveillance scenes. The framework is based on a novel threat assessment algorithm which combines the concept of ownership with automatic understanding of social relations in order to infer abandonment of objects. Implementation is achieved through development of a logic-based inference engine based on Prolog. Threat detection performance is conducted by testing against a range of datasets describing realistic situations and demonstrates a reduction in the number of false alarms generated. The proposed system represents the approach employed in the EU SUBITO project (Surveillance of Unattended Baggage and the Identification and Tracking of the Owner).

Item Type: Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Computing and Information Systems
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Date Deposited: 12 Dec 2014 10:39
URI: http://repository.edgehill.ac.uk/id/eprint/6239

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