Fuzzy integral-based composite facial expression generation for a robotic head

Abstract

Conventional methods produced composite facial expressions by interpolating the representative facial expressions under the assumption that the transitions between facial expressions are linear. Considering the nonlinear property, this paper proposes a fuzzy integral-based method for generating composite facial expressions. Fuzzy measures represent the relationship among emotions and the partial evaluation of current emotion state is obtained from a predefined error function of the ideal basic emotion states and the current emotion state. Fuzzy integral of the partial evaluation with respect to fuzzy measures is employed to globally evaluate the current emotion state for generating composite facial expressions. The effectiveness of the proposed method for generating composite facial expressions is demonstrated through the experiments with a robotic head with 19 degrees of freedom, developed in RIT Laboratory, KAIST.