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DOI: 10.14569/IJACSA.2020.0110781
PDF

Abandoned Object Detection using Frame Differencing and Background Subtraction

Author 1: Mohiu Din
Author 2: Aneela Bashir
Author 3: Abdul Basit
Author 4: Sadia Lakho

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 7, 2020.

  • Abstract and Keywords
  • How to Cite this Article
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Abstract: Tracking objects over fixed surveillance cameras are widely used for security purposes in public areas such as train stations, airports, parking areas, and public transportation for the prevention of terrorism. Once the object is accurately detected in the image scene, we can use various visual algorithms to find a number of applications. In this paper, we introduce a model for tracking the multiple objects along with detecting the abandoned luggage in the real time environment. In our model, we used the initial frames to model the background scene. Next, we used the motion model that is background subtraction to detect and track moving objects such as the owner and the luggage. The proposed model also maintains the position history of moving objects followed by the frame differencing technique to find out the luggage history and detect the abandoned luggage by a human. We have used PETS2006 and PETS2007 dataset for the testing of the proposed system in various indoor and outdoor environments with varying lighting conditions.

Keywords: Object detection; video surveillance; tracking; back-ground subtraction; frame differencing; motion model

Mohiu Din, Aneela Bashir, Abdul Basit and Sadia Lakho, “Abandoned Object Detection using Frame Differencing and Background Subtraction” International Journal of Advanced Computer Science and Applications(IJACSA), 11(7), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110781

@article{Din2020,
title = {Abandoned Object Detection using Frame Differencing and Background Subtraction},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110781},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110781},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {7},
author = {Mohiu Din and Aneela Bashir and Abdul Basit and Sadia Lakho}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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