Computer animation has come a long way during the last decade and is now capable of producing near-realistic rendered 3D computer graphics models of expressive, talking, acting humanoids and other characters inhabiting virtual worlds. However, the component of work that needs to be done by animators and artists in producing these synthetic character performances is quite significant. In this paper, we present an expert system based on fuzzy knowledge bases that helps in moving towards automating the task of animating virtual human heads and faces. Our Virtual Actor (Vactor) framework is based on several subsystems that use mainly fuzzy and a minor degree of non-fuzzy linguistic rules to teach virtual actors to know the emotions and gestures to use in different situations. Theories of emotion, personality, dialogue, and acting, as well as empirical evidence are incorporated into our framework and knowledge bases to produce convincing results.
|Cite as: Karunaratne, S. and Yan, H. (2001). A Fuzzy Rule-Based Interactive Methodology for Training Multimedia Actors. In Proc. Selected papers from Pan-Sydney Area Workshop on Visual Information Processing (VIP2000), Sydney, Australia. CRPIT, 2. Eades, P. and Jin, J., Eds. ACS. 3-9. |
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