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Background subtraction based on logarithm rank function and structured sparsity

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Abstract

Background subtraction is one of the key technologies for recognizing and detecting moving targets in the field of video surveillance. To cope with the dynamic background and slow moving objects, a new background subtraction model with logarithm rank function and structured sparsity was proposed based on Robust Principal Component Analysis (RPCA). In this model, the segmentation and index trees were used to dynamically process the foreground, enhancing the appearance similarity and spatial continuity between the pixels. Then, C(2,1) norm was applied to constrain the sparsity of the image block and to strengthen the structured sparsity of foreground. Finally, the background was constrained by the logarithm rank function, which adaptively scaled the weight of large singular values and considered the influence of different singular values on the rank function. The experimental results show that, compared to the state-of-the-art algorithms, 90% of the F-measure values of the proposed model are the best and 10% are the second best. In addition, our new approach exhibits superior performance in subjective evaluation, particularly in dynamic backgrounds, slow moving targets and camera jitter.

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Acknowledgements

This project is partially supported by the National Natural Science Foundation of China (11961010, 61941111), National Natural Science Foundation of Guangxi Province (2018GXNSFAA138169).

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Authors and Affiliations

  1. School of Mathematics and Computing Science, Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation, Guilin University of Electronic Technology, No. 1, Jinji Road, Guilin, 541004, Guangxi, China

    Ying Ban & Lixia Chen

  2. School of Architecture, Yanching Institute of Technology, No. 45, Yingbin North Road, Langfang, 065201, Hebei, China

    Ying Ban

  3. School of Computer Science and Information Security, Guilin University of Electronic Technology, No. 1, Jinji Road, Guilin, 6541004, Guangxi, China

    Xuewen Wang

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  1. Ying Ban
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  2. Lixia Chen
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Correspondence to Lixia Chen.

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Ban, Y., Chen, L. & Wang, X. Background subtraction based on logarithm rank function and structured sparsity. Multimed Tools Appl 81, 20465–20481 (2022). https://doi.org/10.1007/s11042-022-11916-1

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