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Fast Adjacent LBP Based Background Modeling for Foreground Detection in Video Sequences
Abstract In this paper, we have proposed a background modeling based approach to detect the foreground objects in a video. Often, background has dominant textural behavior with some of the dynamic entities in the background. In order to take care of both, we have proposed a computationally fast variant of LBP namely Fast Adjacent LBP (FA-LBP) for background modeling. The histograms of the proposed variant of LBP learn the new video sequence to model the complex background and accurately differentiate foreground from background. The proposed modeling approach has been tested successfully with different frames of PETS sequences and the time complexity of the proposed model has been found to be much less than that of LBP based modeling, which makes it suitable for real-time implementations.
Fast Adjacent LBP Based Background Modeling for Foreground Detection in Video Sequences
Abstract In this paper, we have proposed a background modeling based approach to detect the foreground objects in a video. Often, background has dominant textural behavior with some of the dynamic entities in the background. In order to take care of both, we have proposed a computationally fast variant of LBP namely Fast Adjacent LBP (FA-LBP) for background modeling. The histograms of the proposed variant of LBP learn the new video sequence to model the complex background and accurately differentiate foreground from background. The proposed modeling approach has been tested successfully with different frames of PETS sequences and the time complexity of the proposed model has been found to be much less than that of LBP based modeling, which makes it suitable for real-time implementations.
Fast Adjacent LBP Based Background Modeling for Foreground Detection in Video Sequences
Acharya, Subhabrata (author) / Nanda, Pradipta Kumar (author)
2019-06-28
9 pages
Article/Chapter (Book)
Electronic Resource
English
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