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Analysis of Facial Emotion Recognition Technology and Its Effectiveness in Human Interaction

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Advances in Interdisciplinary Practice in Industrial Design (AHFE 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 790))

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Abstract

Facial expressions are connected to experiencing emotions according to Facial-Feedback Theory of Emotion developed by Charles Darwin and William James [17]. Knowing how to read and interpret facial expressions helps us understand how human beings connect with one another in mobile-mediated communication (MMC) and improve our own abilities at managing emotions. There have been multiple types of research conducted that study and compare factors that influence facial emotion recognition in humans [10]. As one of the most prominent channel in human interactions, facial expression is a good indicator of a person’s emotions. Recent technological advancements have had a drastic impact on human interaction. Besides face-to-face chat, video chatting become more and more popular in the digital age. This research provides to understand how video, voice and music influence emotion perception in the MMC context among different user groups. In this research, we evaluated challenges and effectiveness between two primary emotions: happiness and sadness in video chatting. This study analyzed the emotional influences of voice and music on video chatting and its effectiveness on sensing others emotional energy. Participants were from 18–42 years old and 98% of participants are in between 18–32 years old. A series of visual stimuli were created with four models were from Gen Z; Millennial; Gen X; and Baby Boomer. In addition, the research examines the comfort level with different relationships (e.g. friends; acquaintances; and strangers) in the video chatting environment.

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Author information

Authors and Affiliations

  1. Department of Art, University of South Dakota, 414 E. Clark St., Vermillion, SD, 57069, USA

    Qiuwen Li

  2. School of Design, South Daktoa State University, 117 Grove Hall, Brookings, SD, 57007, USA

    Young Ae Kim

Authors
  1. Qiuwen Li
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  2. Young Ae Kim
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Corresponding author

Correspondence to Qiuwen Li .

Editor information

Editors and Affiliations

  1. School of Industrial Design, Carleton University, Ottawa, Ontario, Canada

    WonJoon Chung

  2. School of Art & Design, University of Illinois at Urbana Champaign, Champaign, Illinois, USA

    Cliff Sungsoo Shin

Appendices

Appendix A: Survey Visual Stimuli

figure a

Appendix B: Vocal Stimuli

Happiness (Positive)

Sadness (Negative)

I am so excited

You hurt my feeling

Appendix C: Musical Stimuli

Happiness (Positive)

Sadness (Negative)

The lonely man from the incredible hulk

Merrie melodies & looney tunes

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Li, Q., Kim, Y.A. (2019). Analysis of Facial Emotion Recognition Technology and Its Effectiveness in Human Interaction. In: Chung, W., Shin, C. (eds) Advances in Interdisciplinary Practice in Industrial Design. AHFE 2018. Advances in Intelligent Systems and Computing, vol 790. Springer, Cham. https://doi.org/10.1007/978-3-319-94601-6_23

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  • DOI: https://doi.org/10.1007/978-3-319-94601-6_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-94600-9

  • Online ISBN: 978-3-319-94601-6

  • eBook Packages: EngineeringEngineering (R0)

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