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Emotion Recognition Using Eye-Tracking: Taxonomy, Review and Current Challenges.

Jia Zheng Lim1, James Mountstephens2, Jason Teo2

  • 1Evolutionary Computing Laboratory, Faculty of Computing and Informatics, Universiti Malaysia Sabah, Jalan UMS, 88400, Kota Kinabalu, Sabah, Malaysia.

Sensors (Basel, Switzerland)
|April 26, 2020
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Summary

This survey explores emotion recognition using eye-tracking technology, a novel approach in affective computing. It reviews current methods, features, and future research directions for detecting emotions via eye movements.

Keywords:
affective computingemotion engineeringemotion recognitioneye-trackingmachine learning

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Area of Science:

  • Affective Computing
  • Human-Computer Interaction
  • Machine Learning

Background:

  • Emotion detection is a key area in machine learning and affective computing.
  • Traditional methods include electroencephalography (EEG), facial image processing, and speech analysis.
  • Eye-tracking is an emerging sensor modality for emotion detection, often used exclusively.

Purpose of the Study:

  • To provide a comprehensive review of emotion recognition using eye-tracking technology.
  • To categorize and summarize existing literature on this topic.
  • To identify open research problems and future directions in the field.

Main Methods:

  • Reviewing background on emotion modeling and eye-tracking devices.
  • Analyzing emotion stimulation methods and extracting emotional features from eye-tracking data.
  • Categorizing and summarizing relevant scientific literature.

Main Results:

  • Eye-tracking offers a promising, albeit relatively new, approach to emotion detection.
  • Various emotional-relevant features can be extracted from eye-tracking data.
  • A taxonomy of current research in eye-tracking-based emotion recognition is presented.

Conclusions:

  • Eye-tracking is a valuable primary sensor modality for emotion detection.
  • Further research is needed to address open problems and expand the knowledge base.
  • Future directions include refining methods and exploring new applications.