IDEAS home Printed from https://ideas.repec.org/a/epw/ejece0/v6y2022i3id19440.html

A Method of Improving Accuracy in Expression Recognition

Author

Listed:
  • Zhi-Jie Li

    (Dalian Minzu University, China)

Abstract

In order to improve the accuracy of a special kind of facial expression recognition problem, a method for precise face detection and segmentation combined with the particle swarm optimization is proposed. The method uses three key technologies: skin color segmentation, particle swarm search and curve approximation. Firstly, the face contour is roughly obtained through skin color segmentation. Secondly, the accurate face position is detected by particle swarm optimization. Thirdly, the face contour is reduced and regulated further via the curve approximation. The experimental results show that this method can eliminate the interference factor, and then improve the accuracy of expression recognition.

Suggested Citation

  • Zhi-Jie Li, 2022. "A Method of Improving Accuracy in Expression Recognition," European Journal of Electrical Engineering and Computer Science, European Open Science, vol. 6(3), pages 27-30, May.
  • Handle: RePEc:epw:ejece0:v:6:y:2022:i:3:id:19440
    DOI: 10.24018/ejece.2022.6.3.440
    as

    Download full text from publisher

    File URL: https://eu-opensci.org/index.php/ejece/article/view/19440
    File Function: Abstract page
    Download Restriction: no

    File URL: https://eu-opensci.org/index.php/ejece/article/download/19440/11241
    File Function: Full text
    Download Restriction: no

    File URL: https://libkey.io/10.24018/ejece.2022.6.3.440?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:epw:ejece0:v:6:y:2022:i:3:id:19440. 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: support (email available below). General contact details of provider: https://eu-opensci.org/index.php/ejece .

    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.