Active Affective State Detection and User Assistance
نویسندگان
چکیده
Intelligent user assistance systems face challenges of incomplete, uncertain and multiple modality sensory observations, user’s changing internal state, and constraints in making decisions. We introduce a probabilistic framework to dynamically model user’s affective state with various visual cues in such systems. A systematic mechanism performs purposive and sufficing information integration to infer user’s affective state and provide correct assistance. We aim to actively infer the user’s status and engage in appropriate assistance in a timely and efficient manner.
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