出版社：Japan Society for Fuzzy Theory and Intelligent Informatics
摘要：In order to transmit facial expressions of the user using the face of a lifelike agent in agent-mediated distance communication, we have to realize facial expression mapping, which gives synthetic facial expressions of the agent appropriate for representing facial expressions of the user in communication. However, the criterion to determine which expression on the agent's face is the "same" as that on the user's face heavily depends on the subjective view of the user. This article discusses how to learn the facial expression mapping reflecting the user's subjective view from the interaction with the user for agent-mediated communication. In the discussion, we focus on the two problems: how to make the facial expression mapping realized by the system reflect the user's subjective view gradually through the interaction, and how to realize the facial expression mapping with the error less than the range acceptable for the user. We propose an approach that copes with these two problems by (1) acquiring positive examples and negative ones for the facial expression mapping reflecting the user's subjective view from the interaction with the user, (2) estimating the acceptable range of the error to realize the facial expression mapping, and (3) constituting RBF(Radial Basis Function) network that realizes the facial expression mapping within the estimated range of the error.
