The fuzzy emotion recognition framework using semantic-linguistic facial features

Dewi Yanti Liliana, T. Basaruddin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Emotion recognition through facial expression analysis is an emerging research in Artificial Intelligence which faces many challenges. The problem is the variation of facial expressions that displays human emotions. Humans can subjectively express the same emotions in various ways. To overcome the problem of ambiguity in emotion expression, a fuzzy approach is developed to analyze the facial components in determining the type of emotion. In this study, we proposed a framework for fuzzy emotion recognition as a representation of the psychologist knowledge. Three stages in the fuzzy emotion recognition were facial feature extraction with Active Appearance Model; Semantic-linguistic facial features extraction; fuzzy emotion recognition with Fuzzy Emotion Classification. System performance testing provided the best results on extended Cohn Kanade (CK+) facial expression dataset, with the accuracy of linguistic facial component recognition 0.98, and accuracy of fuzzy emotion recognition 0.90. Testing was also performed on custom-made Indonesian Mixed Emotion Dataset (IMED) which resulted in accuracy of 0.87. The fuzzy emotion recognition has a potential to be applied in various real problems such as virtual counseling, stress detection, lie detection, and e-commerce.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728108346
DOIs
Publication statusPublished - Nov 2019
Event2019 IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2019 - Depok, Indonesia
Duration: 12 Nov 201914 Nov 2019

Publication series

NameIEEE Region 10 Humanitarian Technology Conference, R10-HTC
Volume2019-November
ISSN (Print)2572-7621

Conference

Conference2019 IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2019
CountryIndonesia
CityDepok
Period12/11/1914/11/19

Keywords

  • Facial components
  • Facial expression
  • Fuzzy emotion
  • Linguistic features
  • Semantic features

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