Geometric facial components feature extraction for facial expression recognition

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

Abstract

Facial expression recognition is an active research challenge in computer vision and artificial intelligence since facial expressions contribute non-verbal information in human communication. Capturing facial features become an important phase in facial recognition systems. Finding suitable feature descriptor is essential to determine the recognition results. We propose a novel geometric feature extraction method which apply simple calculation techniques for facial components to ensure the robustness for each variation of pose. Unlike any other features which require more efforts in a transformation process, the proposed method efficiently works directly on pixels basis. We apply our proposed features into a facial expression recognition system and validate emotion results on extended Cohn Kanade (CK+) emotion dataset and gives accuracy rate 93.67%.

Original languageEnglish
Title of host publication2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages391-396
Number of pages6
ISBN (Electronic)9781728101354
DOIs
Publication statusPublished - 17 Jan 2019
Event10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018 - Yogyakarta, Indonesia
Duration: 27 Oct 201828 Oct 2018

Publication series

Name2018 International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018

Conference

Conference10th International Conference on Advanced Computer Science and Information Systems, ICACSIS 2018
Country/TerritoryIndonesia
CityYogyakarta
Period27/10/1828/10/18

Keywords

  • Emotion recognition
  • Facial components analysis
  • Facial expression recognition
  • Geometric feature extraction

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