A survey of affect recognition methods: audio, visual and spontaneous expressions

  • Authors:
  • Zhihong Zeng;Maja Pantic;Glenn I. Roisman;Thomas S. Huang

  • Affiliations:
  • University of Illinois at Urbana-Champaign, Urbana, IL;Imperial College London, London, United Kingdom;University of Illinois at Urbana-Champaign, Urbana-Champaign, IL;University of Illinois at Urbana-Champaign, Urbana-Champaign, IL

  • Venue:
  • Proceedings of the 9th international conference on Multimodal interfaces
  • Year:
  • 2007

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Abstract

Automated analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, linguistics, neuroscience, and related disciplines. Promising approaches have been reported, including automatic methods for facial and vocal affect recognition. However, the existing methods typically handle only deliberately displayed and exaggerated expressions of prototypical emotions-despite the fact that deliberate behavior differs in visual and audio expressions from spontaneously occurring behavior. Recently efforts to develop algorithms that can process naturally occurring human affective behavior have emerged. This paper surveys these efforts. We first discuss human emotion perception from a psychological perspective. Next, we examine the available approaches to solving the problem of machine understanding of human affective behavior occurring in real-world settings. We finally outline some scientific and engineering challenges for advancing human affect sensing technology.