Many applications in Computer Graphics contain computationally expensive calculations. These calculations are often performed at many points to produce a full solution, even though the subspace of reasonable solutions may be of a relatively low dimension. The calculation of facial articulation and rendering of scenes with global illumination are two example applications that require these sort of computations. In this paper, we present Key Point Subspace Acceleration and Soft Caching, a technique for accelerating these types of computations.

Key Point Subspace Acceleration (KPSA) is a statistical acceleration
scheme that uses examples to compute a statistical subspace and a set
of characteristic key points. The full calculation is then computed
only at these key points and these points are used to provide a
subspace based estimate of the entire calculation. The soft caching
process is an extension to the KPSA technique where the key points are
also used to provide a confidence estimate for the KPSA result. In
cases with high anticipated error the calculation will then ``fail
through'' to a full evaluation of all points (a cache miss), while
frames with low error can use the accelerated statistical evaluation
(a cache hit).

Paper (PDF)

*Additional materials:* [SiggraphSlides.pdf], [softCaching.mov]

Available in the proceedings of Siggraph 2007

Available as Pixar Technical Memo #06-04b

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