The widely used ambient occlusion (AO) technique provides an approximation of some global illumination effects and is efficient enough for use in real-time applications. Because it relies on computing the visibility from each point on a surface, AO computation is expensive for dynamically deforming objects, such as characters in particular. In this paper, we describe an algorithm for producing high-quality dynamically changing AO for characters. Our fundamental idea is to factorize the AO computation into a coarse-scale component in which visibility is determined by approximating spheres, and a fine-scale component that leverages a skinning-like algorithm for efficiency, with both components trained in a regression against ground-truth AO values. The resulting algorithm accommodates interactions with external objects and generalizes without requiring carefully constructed training data. Extensive comparisons illustrate the capabilities and advantages of our algorithm.
Binh Huy Le, Henrik Halen, Carlos Gonzalez-Ochoa, and JP Lewis. 2019. High-Quality Object-Space Dynamic Ambient Occlusion for Characters using Bi-level Regression. In Symposium on Interactive 3D Graphics and Games (I3D ’19), May 21–23, 2019, Montreal, QC, Canada. ACM, NewYork, NY, USA, 10 pages. https://doi.org/10.1145/3306131.3317029
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