Recognising spontaneous facial micro-expressions

  • Authors:

  • Tomas Pfister; Xiaobai Li;Guoying Zhao;Matti Pietikainen

  • Affiliations:

  • Machine Vision Group, Department of Computer Science and Engineering, University of Oulu, PO Box 4500, 90014, Finland;Machine Vision Group, Department of Computer Science and Engineering, University of Oulu, PO Box 4500, 90014, Finland;Machine Vision Group, Department of Computer Science and Engineering, University of Oulu, PO Box 4500, 90014, Finland;Machine Vision Group, Department of Computer Science and Engineering, University of Oulu, PO Box 4500, 90014, Finland

  • Venue:
  • ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
  • Year:
  • 2011

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Abstract

Facial micro-expressions are rapid involuntary facial expressions which reveal suppressed affect. To the best knowledge of the authors, there is no previous work that successfully recognises spontaneous facial micro-expressions. In this paper we show how a temporal interpolation model together with the first comprehensive spontaneous micro-expression corpus enable us to accurately recognise these very short expressions. We designed an induced emotion suppression experiment to collect the new corpus using a high-speed camera. The system is the first to recognise spontaneous facial micro-expressions and achieves very promising results that compare favourably with the human micro-expression detection accuracy.