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Mixture of Gaussians-Based Background Subtraction for Bayer-Pattern Image Sequences

Title
Mixture of Gaussians-Based Background Subtraction for Bayer-Pattern Image Sequences
Author
정호기
Keywords
Background subtraction; Bayer color filter array; mixture of Gaussians (MoG); visual surveillance
Issue Date
2011-03
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Citation
IEEE transactions on circuits and systems for video technology,Vol.21 No.3 [2011],365-370
Abstract
This letter proposes a background subtraction method for Bayer-pattern image sequences. The proposed method models the background in a Bayer-pattern domain using a mixture of Gaussians (MoG) and classifies the foreground in an interpolated red, green, and blue (RGB) domain. This method can achieve almost the same accuracy as MoG using RGB color images while maintaining computational resources (time and memory) similar to MoG using grayscale images. Experimental results show that the proposed method is a good solution to obtain high accuracy and low resource requirements simultaneously. This improvement is important for a low-level task like background subtraction since its accuracy affects the performance of high-level tasks, and is preferable for implementation in real-time embedded systems such as smart cameras.
URI
http://ieeexplore.ieee.org/document/5604673/
ISSN
1051-8215
DOI
10.1109/TCSVT.2010.2087810
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > AUTOMOTIVE ENGINEERING(미래자동차공학과) > Articles
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