IDEAS home Printed from https://ideas.repec.org/a/igg/jmdem0/v10y2019i4p46-63.html
   My bibliography  Save this article

An Analysis of Human Emotions by Utilizing Wavelet Features

Author

Listed:
  • Soo-Yeon Ji

    (Bowie State University, USA)

  • Bong Keun Jeong

    (Coastal Carolina University, USA)

  • Dong Hyun Jeong

    (University of the District of Columbia, USA)

Abstract

Human emotion recognition is critical to people managing their stress and emotions. Although many innovative techniques have been proposed to recognize human emotions, it is still challenging to understand the emotions due to individual differences in the diversity of emotions. This article focuses on analyzing the emotions computationally. In detail, a wavelet transform technique is utilized to extract significant features and find patterns in an emotion dataset. With the extracted features, both classification and visual analysis are performed. For the classification, Logistic Regression, C4.5, and Support Vector Machine are used. Visualization approaches are also utilized to represent similarities and differences among the emotion patterns. From the analysis, the authors found that the proposed method shows an improvement in identifying the differences among the emotions.

Suggested Citation

  • Soo-Yeon Ji & Bong Keun Jeong & Dong Hyun Jeong, 2019. "An Analysis of Human Emotions by Utilizing Wavelet Features," International Journal of Multimedia Data Engineering and Management (IJMDEM), IGI Global, vol. 10(4), pages 46-63, October.
    • Handle: RePEc:igg:jmdem0:v:10:y:2019:i:4:p:46-63
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJMDEM.2019100103
    Download Restriction: no
    ---><---

    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:igg:jmdem0:v:10:y:2019:i:4:p:46-63. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.