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Surveillance video coding via low-rank and sparse decomposition

Published: 29 October 2012 Publication History

Abstract

Surveillance videos are usually with a static or gradually changed background. The state-of-the-art block-based codec, H.264/AVC, is not sufficiently efficient for encoding surveillance videos since it cannot exploit the strong background temporal redundancy in a global manner. In this paper, motivated by the recent advance on low-rank and sparse decomposition (LRSD), we propose to apply it for the compression of surveillance videos. In particular, the LRSD is employed to decompose a surveillance video into the low-rank component, representing the background, and the sparse component, representing the moving objects. Then, we design different coding methods for the two different components. We represent the frames of the background by very few independent frames based on their linear dependency, which dramatically removes the temporal redundancy. Experimental results show that, for the compression of surveillance videos, the proposed scheme can significantly outperform H.264/AVC, up to 3 dB PSNR gain, especially at relatively low bit rates.

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Cited By

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  • (2023)Hyper RPCA: Joint Maximum Correntropy Criterion and Laplacian Scale Mixture Modeling on-the-Fly for Moving Object DetectionIEEE Transactions on Multimedia10.1109/TMM.2021.312157125(112-125)Online publication date: 2023
  • (2023)Apron surveillance video coding based on compositing virtual reference frame with object libraryIET Image Processing10.1049/ipr2.1281017:8(2475-2488)Online publication date: 20-Apr-2023
  • (2022)Robust Image Hashing With Saliency Map And Sparse ModelThe Computer Journal10.1093/comjnl/bxac010Online publication date: 16-Mar-2022
  • Show More Cited By

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    cover image ACM Conferences
    MM '12: Proceedings of the 20th ACM international conference on Multimedia
    October 2012
    1584 pages
    ISBN:9781450310895
    DOI:10.1145/2393347
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    New York, NY, United States

    Publication History

    Published: 29 October 2012

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    Author Tags

    1. cur decomposition
    2. low-rank and sparse decomposition
    3. surveillance video compression

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    MM '12
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    MM '12: ACM Multimedia Conference
    October 29 - November 2, 2012
    Nara, Japan

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    Overall Acceptance Rate 2,145 of 8,556 submissions, 25%

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    Cited By

    View all
    • (2023)Hyper RPCA: Joint Maximum Correntropy Criterion and Laplacian Scale Mixture Modeling on-the-Fly for Moving Object DetectionIEEE Transactions on Multimedia10.1109/TMM.2021.312157125(112-125)Online publication date: 2023
    • (2023)Apron surveillance video coding based on compositing virtual reference frame with object libraryIET Image Processing10.1049/ipr2.1281017:8(2475-2488)Online publication date: 20-Apr-2023
    • (2022)Robust Image Hashing With Saliency Map And Sparse ModelThe Computer Journal10.1093/comjnl/bxac010Online publication date: 16-Mar-2022
    • (2021)TMCOSS: Thresholded Multi-Criteria Online Subset Selection for Data-Efficient Autonomous Driving2021 IEEE/CVF International Conference on Computer Vision (ICCV)10.1109/ICCV48922.2021.00628(6321-6330)Online publication date: Oct-2021
    • (2019)Periodic Enhanced Frame based Long-short-term Reference in HEVC for Conference and Surveillance Video CodingIEEE Access10.1109/ACCESS.2019.2909270(1-1)Online publication date: 2019
    • (2019)Multisource surveillance video data coding with hierarchical knowledge libraryMultimedia Tools and Applications10.1007/s11042-018-6825-478:11(14705-14731)Online publication date: 1-Jun-2019
    • (2018)Background Modeling and Referencing for Moving Cameras-Captured Surveillance Video Coding in HEVCIEEE Transactions on Multimedia10.1109/TMM.2018.282916320:11(2921-2934)Online publication date: Nov-2018
    • (2018)On the Applications of Robust PCA in Image and Video ProcessingProceedings of the IEEE10.1109/JPROC.2018.2853589106:8(1427-1457)Online publication date: Aug-2018
    • (2018)Video Compression for Object Detection Algorithms2018 24th International Conference on Pattern Recognition (ICPR)10.1109/ICPR.2018.8546064(3007-3012)Online publication date: Aug-2018
    • (2018)Background Error Propagation Model Based RDO in HEVC for Surveillance and Conference Video CodingIEEE Access10.1109/ACCESS.2018.28793296(67206-67216)Online publication date: 2018
    • Show More Cited By

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