IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0308933.html
   My bibliography  Save this article

Optimizing motion detection performance: Harnessing the power of squeeze and excitation modules

Author

Listed:
  • Jabulani Brown Mpofu
  • Chenglong Li
  • Xinyan Gao
  • Xinxin Su

Abstract

This paper introduces an innovative segmentation model that extends the U-Net architecture with a Squeeze and Excitation (SE) mechanism, designed to enhance the detection of moving objects in video streams. By integrating this model into the ViBe motion detection algorithm, we have significantly improved detection accuracy and reduced false positive rates. Our approach leverages adaptive techniques to increase the robustness of the segmentation model in complex scenarios, without requiring extensive manual parameter tuning. Despite the notable improvements, we recognize that further training is necessary to optimize the model for specific applications. The results indicate that our method provides a promising direction for real-time motion detection systems that require high precision and adaptability to varying conditions.

Suggested Citation

  • Jabulani Brown Mpofu & Chenglong Li & Xinyan Gao & Xinxin Su, 2024. "Optimizing motion detection performance: Harnessing the power of squeeze and excitation modules," PLOS ONE, Public Library of Science, vol. 19(8), pages 1-18, August.
    • Handle: RePEc:plo:pone00:0308933
    DOI: 10.1371/journal.pone.0308933
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0308933
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0308933&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0308933?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0308933. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.