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References: 10. Emotion Theory & the Core Expression Set

  1. Paul Ekman - Wikipedia - Biography of the psychologist whose cross-cultural studies identified universally recognized facial expressions and who co-developed the Facial Action Coding System, the research foundation for this chapter's entire expression set.

  2. Facial Action Coding System - Wikipedia - Detailed explanation of how FACS decomposes facial expressions into individual, measurable action units, the same "independent, combinable features" idea this chapter connects to the robot face's eyebrow/eye/mouth parameters.

  3. Emotion classification - Wikipedia - Overview of basic emotion theory, Ekman's six-to-seven universal emotions, and the ongoing scholarly debate over universality, directly supporting this chapter's "research, not settled fact" framing.

  4. Emotions Revealed: Recognizing Faces and Feelings to Improve Communication and Emotional Life (2nd edition) - Paul Ekman - Holt Paperbacks - Ekman's own accessible account of his universal emotions research, with photographs and descriptions of each expression's distinguishing eyebrow, eye, and mouth features.

  5. Unmasking the Face: A Guide to Recognizing Emotions from Facial Expressions - Paul Ekman and Wallace V. Friesen - Malor Books - A practical, illustrated guide to reading happiness, sadness, anger, fear, surprise, disgust, and more from facial muscle movement, foundational to this chapter's expression recipes.

  6. Universal Emotions - Paul Ekman Group - The official Ekman organization's summary of the seven universal emotions (anger, contempt, disgust, enjoyment, fear, sadness, surprise), explaining what makes an emotion "basic" and how each carries a distinctive facial signal.

  7. Facial Action Coding System - Paul Ekman Group - The official description of FACS as "a comprehensive, anatomically based system for describing all visually discernible facial movement," including how action units are used in research, animation, and computer vision.

  8. Deriving Minimal Features for Human-Like Facial Expressions in Robotic Faces - Casey C. Bennett and Selma Sabanovic, International Journal of Social Robotics - A peer-reviewed study testing how few moving features (eyes, eyebrows, mouth) a robot face needs for people to correctly identify an intended emotion, the direct evidence behind Minimal Feature Robot Research.

  9. Introduction to Paul Ekman and His Work - Simply Put Psych - A student-friendly overview of Ekman's career, his cross-cultural universality studies, and how FACS enables objective, muscle-by-muscle analysis of an expression.

  10. Facial Emotion Expressions in Human-Robot Interaction: A Survey - arXiv / International Journal of Social Robotics - An open-access research survey covering how accurately both people and robots recognize facial emotion expressions, and how robots generate expressions by hand-coded or automated methods, relevant to this chapter's discussion of uneven Emotion Recognition Accuracy.