Emotion and sociable humanoid robots
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This paper presents a parallel real time framework for emotion extraction from video fragments of human movements. Its framework is used for tracking of a waving hand by evaluation of moving skin-colored objects. The tracking analysis demonstrates that acceleration and frequency characteristics of the traced objects are relevant for classification of the emotional expressiveness of human movements. The solution is part of a larger project on interaction between a human and a humanoid robot with the aim of training social behavioral skills to autistic children with robots acting in a natural environment.