Improved Facial Realism through an Enhanced Representation of Anatomical Behavior in Sign Language Avatars
Facial movements and expressions are critical features of signed languages, yet are some of the most challenging to reproduce on signing avatars. Due to the relative lack of research efforts in this area, the facial capabilities of such avatars have yet to receive the approval of those in the Deaf community. This paper revisits the representations of the human face in signed avatars, specifically those based on parameterized muscle simulation such as FACS and the MPEG-4 file definition. An improved framework based on rotational pivots and pre-defined movements is capable of reproducing realistic, natural gestures and mouthings on sign language avatars. The new approach is more harmonious with the underlying construction of signed avatars, generates improved results, and allows for a more intuitive workflow for the artists and animators who interact with the system.
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