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Robust abandoned object detection integrating wide area visual surveillance and social context
2013
Pattern Recognition Letters
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
doi:10.1016/j.patrec.2013.01.018
fatcat:tredjkkbsfddzogbvkejikybbm