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Adaptive pixel-block based background subtraction using low-rank and block-sparse matrix decomposition

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Abstract

We present three stages of a novel backgrounds subtraction method in this paper: a new pixel-block based randomized arrangement is utilized to preprocess all the frame images, so that low-rank property of background and sparsity of foreground can be separated more easily; different foreground regions have different sparsity, we use a set of adaptive parameters for subtracting foregrounds according to the variances of frame pixels; finally, background model is built via an improved low-rank and block-sparse matrix decomposition based on the proposed adaptive pixel-block background subtraction. All these key measurements guarantee the considerable performance in background subtraction, which are also demonstrated in our experimental results.

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Acknowledgments

The authors would like to thank the editor and the anonymous reviewers for their valuable and helpful comments, as well as the important guiding significance to our researches. The authors also acknowledge Yichao Cao from Southeast University for his useful proofreading and suggestions.

This work was supported by the National Natural Science Foundation of China (No. 61871123), Key Research and Development Program in Jiangsu Province (No. BE2016739) and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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Correspondence to Xiaobo Lu.

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This work was supported by the National Natural Science Foundation of China (No.61871123), Key Research and Development Program in Jiangsu Province (No.BE2016739) and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.

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Wu, X., Lu, X. Adaptive pixel-block based background subtraction using low-rank and block-sparse matrix decomposition. Multimed Tools Appl 78, 16507–16526 (2019). https://doi.org/10.1007/s11042-018-7037-7

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