Simplifying Character Skins with Analytic Error Metrics

Traditionally, levels of detail (LOD) for animated characters are computed from a single pose. Later techniques refined this approach by considering a set of sample poses and evaluating a more representative error metric. A recent approach to the character animation problem, animation space, (AS) provides a framework for measuring error analytically. The work presented here uses the animation-space framework to derive two new techniques to improve the quality of LOD approximations. First, we use an animation-space distance metric within a progressive mesh-based LOD scheme, giving results that are reasonable across a range of poses, without requiring that the pose space be sampled. Second, we simplify individual vertices by reducing the number of bones that influence them, using a constrained least-squares optimization. This influence simplification is combined with the progressive mesh to form a single stream of simplifications. Influence simplification reduces the geometric error by up to an order of magnitude, and allows models to be simplified further than is possible with only a progressive mesh. Quantitative (geometric error metrics) and qualititative (user perceptual) experiments confirm that these new extensions provide significant improvements in quality over traditional, naı̈ve simplification; and while there is naturally some impact on the speed of the off-line simplification process, it is not prohibitive.