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http://dx.doi.org/10.3745/KTSDE.2013.2.1.027

Background Subtraction Algorithm Based on Multiple Interval Pixel Sampling  

Lee, Dongeun (LG CNS 정보기술연구원)
Choi, Young Kyu (한국기술교육대학교 컴퓨터공학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.2, no.1, 2013 , pp. 27-34 More about this Journal
Abstract
Background subtraction is one of the key techniques for automatic video content analysis, especially in the tasks of visual detection and tracking of moving object. In this paper, we present a new sample-based technique for background extraction that provides background image as well as background model. To handle both high-frequency and low-frequency events at the same time, multiple interval background models are adopted. The main innovation concerns the use of a confidence factor to select the best model from the multiple interval background models. To our knowledge, it is the first time that a confidence factor is used for merging several background models in the field of background extraction. Experimental results revealed that our approach based on multiple interval sampling works well in complicated situations containing various speed moving objects with environmental changes.
Keywords
Background Subtraction; Motion Detection; Sampling-Based Algorithm; Multiple Interval Sampling;
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