Send in the Clones.(Product Announcement)

An animation-cloning technique gives facial models something to smile about

"Reduce, reuse, recycle." The battle cry of environmentalists may soon be the mantra of computer animators. The expression is an apt description of a technique developed by researcher Junyon Noh under the direction of professor Ulrich Neumann in the Computer Graphics and Immersive Technologies (CGIT) lab at the University of Southern California. Noh has created a system for efficiently transferring existing facial animation sequences from one character model to another, regardless of the different geometric proportions and mesh structures.

The system, called expression cloning, preserves the relative motions, dynamics, and character of the original model by extracting critical vertex information. It then retargets the collected "skeletal" data onto the new model.

Rather than supplanting existing facial-animation techniques, expression cloning is designed to complement them. "Many techniques can produce very nice facial animations. Toy Story and more recently Final Fantasy are good examples," says Noh. But such high quality does not come cheap or easy. "Depending on the techniques employed, ]such animation] requires computationally demanding physical simulation, non-intuitive parameter estimation, artistic talent, and manual tuning," he says. "And most of these efforts are not transferable across models, so the same process has to be repeated for new face models, even for similar animations."

By contrast, expression cloning enables animators to reapply the facial animations they've painstakingly created using any technique to countless models. "Since it is a fast, almost fully automated process, [expression cloning] lets animators save previous efforts to compile a high-quality facial animation library for later use," says Noh.

The heart of the new system is an algorithm that computes surface correspondences between two different face models, which ensures that the source model motions are applied to the correct regions on the target model. "Although it is obvious to humans where the forehead, nose, and mouth are, it is not the case with computers," says Noh. Thus, the algorithm is applied to find such features on the face, align them between the two models, and estimate the surface correspondences.

After this preliminary information has been collected, the system transfers the facial motions for each corresponding face point. Because the geometric proportions of the face models are typically different, the system must adjust the motion at each face point. "The motion adjustment is crucial. Without it, the resulting animation may not be well suited to the target model," says Noh. "The adjustment guarantees that a smile of the person with the big mouth will be scaled down for the person with the smaller mouth."