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What is Facial Expression Classification

Handbook of Research on Synthetic Emotions and Sociable Robotics: New Applications in Affective Computing and Artificial Intelligence
In machine vision, the automatic labelling of facial images or sequences of images with a semantic label or labels describing affect portrayed by the face. Our paper suggests that research has come to focus on a narrowly defined version of this problem: namely the hard classification of facial images (or sequences) into the stereotypical Ekman universal facial expressions, and that researchers in pattern recognition and human-computer interaction could profit by more broadly framing the research domain.
Published in Chapter:
Facial Expression Analysis, Modeling and Synthesis: Overcoming the Limitations of Artificial Intelligence with the Art of the Soluble
Christoph Bartneck (Eindhoven University of Technology, The Netherlands) and Michael J. Lyons (Ritsumeikan University, Japan)
DOI: 10.4018/978-1-60566-354-8.ch003
Abstract
The human face plays a central role in most forms of natural human interaction so we may expect that computational methods for analysis of facial information, modeling of internal emotional states, and methods for graphical synthesis of faces and facial expressions will play a growing role in human-computer and human-robot interaction. However, certain areas of face-based HCI, such as facial expression recognition and robotic facial display have lagged others, such as eye-gaze tracking, facial recognition, and conversational characters. Our goal in this paper is to review the situation in HCI with regards to the human face, and to discuss strategies, which could bring more slowly developing areas up to speed. In particular, we are proposing the “The Art of the Soluble” as a strategy forward and provide examples that successfully applied this strategy.
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