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The Development of a Facial-Affect Recognition System for Application in Human-Robot Interaction Scenarios

[+] Author Affiliations
David Schacter, Christopher Wang, Goldie Nejat, Beno Benhabib

University of Toronto, Toronto, ON, Canada

Paper No. DETC2011-48195, pp. 865-873; 9 pages
doi:10.1115/DETC2011-48195
From:
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 31st Computers and Information in Engineering Conference, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5479-2
  • Copyright © 2011 by ASME

abstract

This paper presents a non-contact unique automated affect recognition system that identifies human facial expressions and classifies them using Support Vector Regression (SVR) into affective states based on a pleasure-arousal two-dimensional model of affect. By utilizing a continuous two-dimensional model, rather than a traditional discrete categorical model for affect, the proposed system captures complex and ambiguous emotions that are prevalent in real-world scenarios. Our aim is to incorporate the proposed recognition system in robots engaged in human-robot interaction (HRI) scenarios. Namely, the system can be utilized by a robot to recognize, in real-time, spontaneous natural facial expressions of a variety of individuals in response to environmental and interactive stimuli. Preliminary experiments demonstrate the system’s ability to recognize affect from a number of individuals displaying different facial expressions.

Copyright © 2011 by ASME

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