Considering the work needed for constructing muscle models artificially

setting their control nodes

and adjusting their computer parameters

we present a method to construct the muscle model automatically and to generate the model calculation parameters for 3D facial animation. We developed a robust facial features recognition algorithm to extract the geometry and texture feature vertices. In the geometry feature recognition process

we adopt synthetically several constraints related to the Gaussian curvature and surface normal value to extract the candidate vertices. In the texture feature recognition process

we use the Gaussian Mixture Model of CrCgCb to extract the feature vertices. Then

clustering procedures are applied to gain the final feature vertices. Finally

using the 13 geometry feature vertices and 8 texture feature vertices extracted by the recognition algorithm

we automatically construct the muscle models for the real-time facial animation.The experimental results demonstrate a matching rate over 90% compared with the landmark vertices made by an artist. The application work indicates that the process of automated muscle model construction based on the feature recognition algorithm fit in with different human head geometries very well. On this basis

we synthesize a group of characteristic facial expressions and mouth shapes with higher realism in real time.