Affective Computing and Intelligent Interaction

Volume 3784 of the series Lecture Notes in Computer Science pp 32-39

Towards Unsupervised Detection of Affective Body Posture Nuances

  • P. Ravindra De SilvaAffiliated withDatabase Systems Laboratory, University of Aizu
  • , Andrea KleinsmithAffiliated withDatabase Systems Laboratory, University of Aizu
  • , Nadia Bianchi-BerthouzeAffiliated withDatabase Systems Laboratory, University of Aizu

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Recently, researchers have been modeling three to nine discrete emotions for creating affective recognition systems. However, in every day life, humans use a rich and powerful language for defining a large variety of affective states. Thus, one of the challenging issues in affective computing is to give computers the ability to recognize a variety of affective states using unsupervised methods. In order to explore this possibility, we describe affective postures representing 4 emotion categories using low level descriptors. We applied multivariate analysis to recognize and categorize these postures into nuances of these categories. The results obtained show that low-level posture features may be used for this purpose, leaving the naming issue to interactive processes.