Hierarchical Retargetting of Fine Facial Motions

We present a novel technique for retargetting captured facial animation to new facial models. We use dense motion data that can express fine motions such as wrinkles. We use a normal mesh, which is a special multi-resolution mesh, to represent source and target models. A normal mesh is defined by the base mesh and sequence of normal offsets from it. Our retargetting consists of two steps: base mesh and detail mesh retargetting. For base mesh retargetting, we use an example-based technique to take advantage of the intuition of the user in specifying the similarity between source and target expressions. In detail mesh retargetting, the variations of normal offsets in the source mesh are hierarchically computed and transferred to the target mesh. Our retargetting scheme is able to produce robust and delicate results for unusual target models from highly detailed motion data.