IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i23p3096-d692321.html
   My bibliography  Save this article

A Soft-YoloV4 for High-Performance Head Detection and Counting

Author

Listed:
  • Zhen Zhang

    (School of Computer Science and Engineering, Huizhou University, Huizhou 516007, China)

  • Shihao Xia

    (School of Computer Science and Engineering, Huizhou University, Huizhou 516007, China)

  • Yuxing Cai

    (School of Computer Science and Engineering, Huizhou University, Huizhou 516007, China)

  • Cuimei Yang

    (School of Computer Science and Engineering, Huizhou University, Huizhou 516007, China)

  • Shaoning Zeng

    (Yangtze Delta Region Institute, University of Electronic Science and Technology of China, Huzhou 313000, China)

Abstract

Blockage of pedestrians will cause inaccurate people counting, and people’s heads are easily blocked by each other in crowded occasions. To reduce missed detections as much as possible and improve the capability of the detection model, this paper proposes a new people counting method, named Soft-YoloV4, by attenuating the score of adjacent detection frames to prevent the occurrence of missed detection. The proposed Soft-YoloV4 improves the accuracy of people counting and reduces the incorrect elimination of the detection frames when heads are blocked by each other. Compared with the state-of-the-art YoloV4, the AP value of the proposed head detection method is increased from 88.52 to 90.54%. The Soft-YoloV4 model has much higher robustness and a lower missed detection rate for head detection, and therefore it dramatically improves the accuracy of people counting.

Suggested Citation

  • Zhen Zhang & Shihao Xia & Yuxing Cai & Cuimei Yang & Shaoning Zeng, 2021. "A Soft-YoloV4 for High-Performance Head Detection and Counting," Mathematics, MDPI, vol. 9(23), pages 1-11, November.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:23:p:3096-:d:692321
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/23/3096/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/9/23/3096/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    head detection; YoloV4; NMS; soft-NMS; people counting;
    All these keywords.

    JEL classification:

    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:gam:jmathe:v:9:y:2021:i:23:p:3096-:d:692321. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.