NDLI: Layered Video Objects Detection Based on LBP and Codebook

Content Provider	IEEE Xplore Digital Library
Author	Yu Wu Delong Zeng Hongbo Li
Copyright Year	2009
Abstract	Background subtraction is often one of the first tasks and a critical part of the machine vision systems. Background modeling methods that only utilize image blocks or pixels suffer from unacceptable false negative detecting rate. A novel layered background modeling method is proposed in objects detecting. First, every block on the first layer is modeled via texture based on local binary pattern (LBP) operators. Then the modeling granularity is deflated onto the second layer to model via codebook. Layered match is done from top down when a new video frame enters. Experimental results prove that the proposed novel approach is useful and robust. It efficiently avoids the false negative detection rate in the pixel-based background modeling when the object color is similar to the background, and also stops the false positives occurring on the contour areas of the moving objects due to the block model.
Starting Page	207
Ending Page	213
File Size	760468
Page Count	7
File Format	PDF
ISBN	9781424435814
DOI	10.1109/ETCS.2009.54
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-07
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Background model Educational technology Face detection Computer science Local binary pattern Codebook Machine vision Object detection Apertures Probability density function Robustness Computer science education Pixel
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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