Background Subtraction

Background Subtraction

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Background subtraction is a widely used concept for detection of moving objects in videos. In the last two decades there has been a lot of development in designing algorithms for background subtraction, as well as wide use of these algorithms in various important applications, such as visual surveillance, sports video analysis, motion capture, etc. Various statistical approaches have been proposed to model scene backgrounds. The concept of background subtraction also has been extended to detect objects from videos captured from moving cameras. This book reviews the concept and practice of background subtraction. We discuss several traditional statistical background subtraction models, including the widely used parametric Gaussian mixture models and non-parametric models. We also discuss the issue of shadow suppression, which is essential for human motion analysis applications. This book discusses approaches and tradeoffs for background maintenance. This book also reviews many of the recent developments in background subtraction paradigm. Recent advances in developing algorithms for background subtraction from moving cameras are described, including motion-compensation-based approaches and motion-segmentation-based approaches.None of these cues byitself is enough to solve the problem, and, therefore, integratingthese four cues, besides high-level ... Apparent 2D motion (optical flow ) is also not enough to properly segment objects; for example an articulated object willanbsp;...


Title:Background Subtraction
Author: Ahmed Elgammal
Publisher:Morgan & Claypool Publishers - 2014-12-01
ISBN-13:

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