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Abandoned Object Detection via Temporal Consistency Modeling for Visual Surveillance

Vishal A. Wankhede, Dhananjay J. Pawar, Mahadeo D. Kokate


This paper introduces a successful approach for distinguishing abandoned luggage in surveillance recordings. We join short- and long-term foundation models to concentrate on closer view of objects, where every pixel in an information picture is named a 2 bit code. In this manner, we acquaint a structure with recognized static frontal areas in light of the worldly move of code designs, and to figure out if the applicant districts contain surrendered protests by breaking down the back-followed directions of baggage proprietors. The trial comes about acquired in light of video pictures from 2006 performance evaluation of tracking and surveillance, and 2007 advanced video and signal-based surveillance databases demonstrate that the proposed approach is successful for identifying relinquished gear, and that it outflanks past techniques.

Cite this Article. Wankhede Vishal A, Pawar Dhananjay J, Kokate Mahadeo D. Abandoned Object Detection via Temporal Consistency Modeling for Visual Surveillance. Research & Reviews: A Journal of Embedded System & Applications. 2017; 5(2): 1–6p

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