Simulating believable facial animation is a topic of
increasing interest in computer graphics and visual
effects. In this paper we present a hybrid technique for
the generation of facial animation based on motion
capture data. After capturing a range of facial expressions
defined by Facial Action Coding System (FACS), the
radial basis function (RBF) is used to transfer the motion
data onto two facial models, one realistic and one stylized.
The calculations of the distances for the RBF technique
are approached in three variants: Euclidean-based,
geodesic mesh-based and hybrid-based. The last one
takes the advantages of the first two approaches. In order
to raise the efficiency, the calculations are aided by preprocessed distance data. The results are then evaluated in
a quantitative and qualitative manner, comparing the
animation outcomes with the real footage. Our findings
show the efficiency of the hybrid technique when
generating facial animation with motion capture
