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 proceedingConference contribution

6 Citations (Scopus)
375 Downloads (Pure)

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 publication2018 IEEE International Conference on Pervasive Computing and Communications: Proceedings
Publisher IEEE
Pages627-632
Number of pages6
ISBN (Electronic)978-1-5386-3227-7
ISBN (Print)978-1-5386-3228-4
DOIs
Publication statusEarly online date - 08 Oct 2018
Event16th IEEE International Conference on Pervasive Computing and Communications - Athens, Greece
Duration: 19 Mar 201823 Mar 2018

Conference

Conference16th IEEE International Conference on Pervasive Computing and Communications
Abbreviated titlePerCom 2018
CountryGreece
CityAthens
Period19/03/201823/03/2018

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