Recognizing, Fast and Slow: Complex Emotion Recognition with Facial Expression Detection and Remote Physiological Measurement

Yi Chiao Wu, Li Wen Chiu, Chun Chih Lai, Bing Fei Wu, Sunny S.J. Lin

Research output: Contribution to journalArticlepeer-review

Abstract

Complex emotion is an aggregate of two or more others which has highly variable appearances, inter-dependence, and affective dynamics.These properties make the recognition hard to handle via existing recognition techniques like action units or valence-arousal detection. In this study, we propose a bionic two-system structure for complex emotion recognition. The structure mimics the working theory of the human brain responding to problems decision-making. System I is a fast compound sensing module. System II is a slower cognitive decision module that processes data more integratively. System I contains one branch for facial expression feature representation including basic emotion, action units, and valence arousal detection and one for physiological measurement which is an image-only implementation for practicality. In System II, a decision module with segmentation is employed to ensure the chosen period including the emotion occurrence and iteratively optimize the emotion information in a given segment via reinforcement learning. The proposed method outperforms state-of-the-art on emotion recognition tasks with an accuracy of 94.15% in basic emotion recognition on the BP4D and an accuracy of 68.75% for binary valence arousal classification on the DEAP. For a subset of complex emotions, the recognition accuracy exceeds 70% on both databases, that is a significant improvement.

Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalIEEE Transactions on Affective Computing
DOIs
StateAccepted/In press - 2023

Keywords

  • action unit detection
  • complex emotion recognition
  • Emotion recognition
  • Face recognition
  • Faces
  • facial expression detection
  • Gold
  • heart rate variability
  • Physiology
  • reinforcement learning
  • remote photoplethysmography
  • Sensors
  • Task analysis
  • valence-arousal detection

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