Transformasi Ruang 3D Pada Animasi Expresi Wajah Avatar Berbasis Radial Basis Function

Abstract

One technique for forming facial animations on avatars is by reusing existing animations, either from other avatar animations or animations from motion data obtained using facial motion capture. This research focuses on the transformation of 3D space for the formation of facial animations on avatars in games or animated films. The transformation is carried out from motion capture data into a 3D avatar face model with 3 face models, namely the human face model, the swan face model and the anoman face model. The motion capture data is transferred according to the feature points of the face model. The results obtained by the facial model feature points will have animations that match the motion capture data. Of the 3 target face models used, the animation results with registration on the human face model have an average standard deviation is 0,0510. The goose face model has an average standard deviation is 0.0034 and the anoman face model has an average standard deviation is 0,0024. With this technique, it is hoped that the formation of facial expression animation on Avatar can be done more quickly because of the reuse of facial motion capture data.