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A bi-modal emotion recognition approach is proposed for recognition of four emotions that integrate information from gestures and speech. The outputs from two uni-modal emotion recognition systems based on affective speech and expressive gesture are fused on a decision level fusion by using weight criterion fusion and best probability plus majority vote fusion methods, and the performance of classifier...
A fuzzy logic based multi-modal gesture recognition method is proposed, where both camera images and hand motion data (given by a 3D acceleration sensor put on human wrists) are used to notify the emotion of humans to robots in real time. To demonstrate the validity, it is applied to a part of the home party scenario enjoyed by five eye robots and four human participants, where 8 types of human emotional-gestures...
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