Accuracy of three commercial automatic emotion recognition systems across different individuals and their facial expressions

Damien Dupré, Nicole Andelic, Gawain Morrison, Gary McKeown

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)

4 Citations (Scopus)

Abstract

Automatic facial expression recognition systems can provide information about our emotions and how they change over time. However, based on different statistical methods the results of automatic systems have not yet been compared. In the current paper we evaluate the emotion detection between three different commercial systems (i.e.Affectiva, Kairos and Microsoft) when detecting dynamic and spontaneous facial expressions. Even if the study was performed on a limited sample of videos, the results show significant differences between the systems for the same video and per system across comparable facial expressions. Finally, we reflect on the implications according the generalization of the results provided by automatic emotion detection.
Original languageEnglish
Title of host publicationPervasive Computing and Communications Workshops (PerCom)
Subtitle of host publicationIEEE Annual Conference
PublisherIEEE Press
Number of pages6
ISBN (Print)978-1-5386-3228-4
DOIs
Publication statusPublished - 8 Oct 2018
Event2018 IEEE International Conference on Pervasive Computing and Communications Workshops : PerCom Workshops 2018 - Athens, Greece
Duration: 19 Mar 201823 Mar 2018

Conference

Conference2018 IEEE International Conference on Pervasive Computing and Communications Workshops
CountryGreece
CityAthens
Period19/03/1823/03/18

Keywords

  • emotion
  • facial expression
  • automatic recognition

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    Dupré, D., Andelic, N., Morrison, G., & McKeown, G. (2018). Accuracy of three commercial automatic emotion recognition systems across different individuals and their facial expressions. In Pervasive Computing and Communications Workshops (PerCom): IEEE Annual Conference IEEE Press. https://doi.org/10.1109/PERCOMW.2018.8480127