International Journal of Science , Engineering and Management (IJSEM)

Monthly Journal for Science , Engineering and Management

Volume3,February 2018,

Topic : Overview of Background Subtraction Algorithms

Authors:Prachi A. Joshi || Dr.R.A.Khan, S.C.Nandedkar

Abstract:Understanding the human activity from the video is proved to be important research area in computer vision since last few years. Background subtraction is a widely used technique for detecting moving objects in videos from static cameras. This approach is said to be the fast way of localizing moving objects in a video frame shot by the static camera which can be used for various computer vision applications. The mentioned technique is used for calculating the foreground mask performing a subtraction between the current frame and a background model, containing the static part of the scene. Here regions of interest are objects like humans, cars, text etc. in its foreground. The objective here is of detecting the moving objects from the difference between the current frame and a reference frame, frequently called as background model or image. Background subtraction algorithms are more popular nowadays because of its computational efficiency in applications like video surveillance, traffic monitoring, human-computer interaction etc. The conditions like moving background, temporarily stationary objects, objects shadows, illumination variation can affect the background subtraction. This paper focuses on the comparative study of different background subtraction algorithms. .

Keywords: Background Subtraction, Human Computer Interaction, Object Detection, Regions of interest, Traffic Monitoring, Video Surveillance, Frame Difference, Mean Filter, Approximate Median Filter, Mixture of Gaussian Model, Running Gaussian Average.

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DOI: 01.1617/vol5/iss2/pid91438


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Editor-in-Chief

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Dr.Muhammad Ishtiaq,
Mirpur University of
Science & Technology,
Mirpur, Azad Kasmir.

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IMPACT FACTOR: 2.7

ISSN(Online): 2456-1304

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJSEM
Electronic ISSN : 2456-1304
Impact Factor : 2.7
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