The Maskle: Automatic Weighting for Facial Animation - An Automated Approach the Problem of Facial Weighting for Animation

Facial animation of 3D characters is frequently a time-consuming and repetitive process that involves either skeleton-rigging or pose-setting for morph targets. A major issue of concern is the necessity to repeat similar tasks for different models, re-creating the same animation system for several faces. Thus there is a need for reusable methods and tools that allow the introduction of automation into these processes. In this paper we present such a method to assist in the process of facial rigging: the Maskle. Based upon the standard bone-weight linear skinning animation technique, the desired distribution of vertex-movement weights for facial animation is pre-programmed into a low-resolution, generic facial mask. This mask, or ‘Maskle’, is then semi-automatically overlaid onto a newly created face model, before the animation-weight distribution is automatically transferred from the Maskle to the model. The result is a weight-painted model, created semi-automatically, and available for the artist to use for animation. We present results comparing Maskle-weighted faces to those weighted manually by an artist, which were treated as the gold standard. The results show that the Maskle is capable of automatically weight-painting a face to within 1.58% of a manually weighted face, with a maximum error of 3.82%. Comparison with standard professional automatic weighting algorithms shows that the Maskle is over three times more accurate.