Abstract: 3D facial animation is a highly important but difficult task in computer graphics area.An effective approach on editing and synthesis of 3D facial animation is proposed.By the approach,users are enabled to assign constraints of facial movement through simple interaction in 2D screen space.A prior probabilistic model is trained by our system using facial animation data.With such a prior model,we propagate the user constraints to the whole 3D facial mesh to generate complete and lifelike facial expressions.By using Isomap learning algorithm,we model the knowledge of 3D facial animation.Incorporating the user specified key frames as end points,a smooth geodesic curve on the high dimensional space of facial animation data is approximated to produce novel animation sequence.Experimental results show that by the proposed method we can intuitively control the synthesis of facial animation and produce vivid expressional animation.