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http://dx.doi.org/10.5370/JEET.2015.10.1.372

Background Subtraction in Dynamic Environment based on Modified Adaptive GMM with TTD for Moving Object Detection  

Niranjil, Kumar A. (Dept. of Electronics and Communication Engineering, P.S.R.Rengasamy College of Engineering for Women Sivakasi)
Sureshkumar, C. (Dept. of Computer Science and Engineering, J.K.K.Nattraja College of Engineering and Technology)
Publication Information
Journal of Electrical Engineering and Technology / v.10, no.1, 2015 , pp. 372-378 More about this Journal
Abstract
Background subtraction is the first processing stage in video surveillance. It is a general term for a process which aims to separate foreground objects from a background. The goal is to construct and maintain a statistical representation of the scene that the camera sees. The output of background subtraction will be an input to a higher-level process. Background subtraction under dynamic environment in the video sequences is one such complex task. It is an important research topic in image analysis and computer vision domains. This work deals background modeling based on modified adaptive Gaussian mixture model (GMM) with three temporal differencing (TTD) method in dynamic environment. The results of background subtraction on several sequences in various testing environments show that the proposed method is efficient and robust for the dynamic environment and achieves good accuracy.
Keywords
Background subtraction; Foreground detection; Video surveillance; Dynamic background; Moving object detection; Video segmentation;
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