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  • 2015

  • Castellano, Ginevra; Gunes, Hatice; Peters, Christopher; Schuller, Björn (2015) : Multimodal affect recognition for naruralistic human-computer and human-robot interactions In: Calvo, Rafael A.; D’Mello, Sidney K.; Gratch, Jonathan; Kappas, Arvid (Hg.): The Oxford handbook of affective computing. Unter Mitarbeit von Rafael A. Calvo, Sidney K. D’Mello, Jonathan Gratch und Arvid Kappas: New York, NY: Oxford University Press (Oxford library of psychology), S. 246-257

    Abstract: This chapter provides a synthesis of research on multimodal affect recognition and discusses methodological considerations and challenges arising from the design of a multimodal affect recognition system for naturalistic human-computer and human-robot interactions. Identified challenges include the collection and annotation of spontaneous affective expressions, the choice of appropriate methods for feature representation and selection in a multimodal context, and the need for context sensitivity and for classification schemes that take into account the dynamic nature of affect and the relationship between different modalities. Finally, two examples of multimodal affect recognition systems used in (soft) real-time naturalistic human-computer and human-robot interaction frameworks are presented. (PsycINFO Database Record (c) 2019 APA, all rights reserved)

    Keywords: Angemessen(heit) (von Technik), Computers, context sensitivity, Face Perception, feature representation, Human Computer Interaction, Human robot interaction, Human-computer interaction, human-robot interaction, multimodal affect recognition, Recognition (Learning), Robotics, selection
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