Abstract
Facial expression and hand gesture analysis plays a fundamental part in emotionally rich man-machine interaction (MMI) systems, since it employs universally accepted non-verbal cues to estimate the users’ emotional state. In this paper, we present a systematic approach to extracting expression related features from image sequences and inferring an emotional state via an intelligent rule-based system. MMI systems can benefit from these concepts by adapting their functionality and presentation with respect to user reactions or by employing agent-based interfaces to deal with specific emotional states, such as frustration or anger.
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Balomenos, T., Raouzaiou, A., Ioannou, S., Drosopoulos, A., Karpouzis, K., Kollias, S. (2005). Emotion Analysis in Man-Machine Interaction Systems. In: Bengio, S., Bourlard, H. (eds) Machine Learning for Multimodal Interaction. MLMI 2004. Lecture Notes in Computer Science, vol 3361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30568-2_27
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DOI: https://doi.org/10.1007/978-3-540-30568-2_27
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