Animating blendshape faces by cross-mapping motion capture data
I3D '06 Proceedings of the 2006 symposium on Interactive 3D graphics and games
Towards higher quality character performance in previz
Proceedings of the Symposium on Digital Production
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Synchronizing the lip and mouth movements naturally along with animation is an important part of convincing 3D character performance. We present a simple, portable and editable lip-synchronization method that works for multiple languages, requires no machine learning, can be constructed by a skilled animator, runs in real time, and can be personalized for each character. Our method associates animation curves designed by an animator on a fixed set of static facial poses, with sequential pairs of phonemes (diphones), and then stitch the diphones together to create a set of curves for the facial poses. Diphone- and triphone-based methods have been explored in various previous works [Deng et al. 2006], often requiring machine learning. However, our experiments have shown that diphones are sufficient for producing high-quality lip syncing, and that longer sequences of phonemes are not necessary. Our experiments have shown that skilled animators can sufficiently generate the data needed for good quality results. Thus our algorithm does not need any specific rules about coarticulation, such as dominance functions [Cohen and Massaro 1993] or language rules. Such rules are implicit within the artist-produced data. In order to produce a tractable set of data, our method reduces the full set of 40 English phonemes to a smaller set of 21, which are then annotated by an animator. Once the full diphone set of animations has been generated, it can be reused for multiple characters. Each additional character requires a small set of eight static poses or blendshapes. In addition, each language requires a new set of diphones, although similar phonemes among languages can share the same diphone curves. We show how to reuse our English diphone set to adapt to a Mandarin diphone set.