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Background Subtraction, Moving Object Detection, Video Surveillance, Mean Filtering, Median Filtering, W4 System, Frame Differencing, Running Gaussian Average, Gaussian Mixture Model, Eigen Background
There are many methods proposed for Back-ground Subtraction algorithm in past years. Background subtraction algorithm is widely used for real time moving object detection in video surveillance system. In this paper we have studied and implemented different types of meth-ods used for segmentation in Background subtraction algo-rithm with static camera. This paper gives good under-standing about procedure to obtain foreground using exist-ing common methods of Background Subtraction, their complexity, utility and also provide basics which will useful to improve performance in the future . First, we have explained the basic steps and procedure used in vision based moving object detection. Then, we have debriefed the common methods of background subtraction like Sim-ple method, statistical methods like Mean and Median filter, Frame Differencing and W4 System method, Running Gaussian Average and Gaussian Mixture Model and last is Eigenbackground Model. After that we have implemented all the above techniques on MATLAB software and show some experimental results for the same and compare them in terms of speed and complexity criteria.
Priyank Shah, Hardik Modi,"Comprehensive Study and Comparative Analysis of Different Types of Background Sub-traction Algorithms", IJIGSP, vol.6, no.8, pp.47-52, 2014. DOI: 10.5815/ijigsp.2014.08.07
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