Review on Real Time Background Extraction: Models, Applications, Environments, Challenges and Evaluation Approaches

Authors

  • Maryam A. Yasir University of Baghdad
  • Yossra Hussain Ali University of Technology

DOI:

https://doi.org/10.3991/ijoe.v17i02.18013

Keywords:

Video surveillance, Background extraction, Foreground object, Evaluation metrics

Abstract


In the computer vision, background extraction is a promising technique. It is characterized by being applied in many different real time applications in diverse environments and with variety of challenges. Background extraction is the most popular technique employed in the domain of detecting moving foreground objects taken by stationary surveillance cameras. Achieving high performance is required with many perspectives and demands. Choosing the suitable background extraction model plays the major role in affecting the performance matrices of time, memory, and accuracy.

In this article we present an extensive review on background extraction in which we attempt to cover all the related topics. We list the four process stages of background extraction and we consider several well-known models starting with the conventional models and ending up with the state-of-the art models. This review also focuses on the model environments whether it is human activities, Nature or sport environments and illuminates on some of the real time applications where background extraction method is adopted. Many challenges are addressed in respect to environment, camera, foreground objects, background, and computation time. 

In addition, this article provides handy tables containing different common datasets and libraries used in the field of background extraction experiments. Eventually, we illustrate the performance evaluation with a table of the set performance metrics to measure the robustness of the background extraction model against other models in terms of time, accurate performance and required memory.

Author Biographies

Maryam A. Yasir, University of Baghdad

Maryam A. Yasir received her bachelor's degree in computer science from the University of Baghdad (UOB) -Iraq 2004. Since 2008, she is working as a lecturer at the computer science department, college of science, University of Baghdad up till now. In 2011 she received a certificate for a seven months course in IT Administration from the Technische Universität Berlin (TU)Berlin-Germany. In 2014 she received her master's degree in computer science from University Putra Malaysia (UPM)-Malaysia. Meanwhile, she is a PhD candidate at the University of Technology (UOT) -Iraq. Maryam has participated in many scholar courses and activities, local and abroad including Fulbright visiting scholar at the University of Central Oklahoma (UCO)-US 2015.

Yossra Hussain Ali, University of Technology

Assistant Professor Dr. Yossra Hussain Ali. She received her B.Sc , M.Sc and PhD degrees in 1996, 2002 and 2006 respectively from Iraq, University of technology, department of Computer Sciences. She Joined the University of Technology, Iraq in 1997. During her postgraduate studies, she worked on Computer Network, Information systems, Agent Programming and Image Processing as well as some experience in Artificial Intelligent and Computer Data Security.  She is a reviewer at many conferences and journals and she supervised a number of undergraduates and postgraduates (PhD. and MSc.) dissertations in Computer sciences. Yossra has many professional certificates and she has published in well regarded journals.

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Published

2021-02-12

How to Cite

Yasir, M. A., & Ali, Y. H. (2021). Review on Real Time Background Extraction: Models, Applications, Environments, Challenges and Evaluation Approaches. International Journal of Online and Biomedical Engineering (iJOE), 17(02), pp. 37–68. https://doi.org/10.3991/ijoe.v17i02.18013

Issue

Section

Papers