In this paper we introduce unique publicly available dense anisotropic BRDF data measurements. We use this dense data as a reference for performance evaluation of the proposed BRDF sparse angular sampling and interpolation approach. The method is based on sampling of BRDF subspaces at fixed elevations by means of several adaptively-represented, uniformly distributed, perpendicular slices. Although this proposed method requires only a sparse sampling of material, the interpolation provides a very accurate reconstruction, visually and computationally comparable to densely measured reference. Due to the simple slices measurement and method's robustness it allows for a highly accurate acquisition of BRDFs. This in comparison with standard uniform angular sampling, is considerably faster yet uses far less samples.
In this paper we will address the problem of fast construction of spatial hierarchies for ray tracing with applications in animated environments including non-rigid animations. We will discuss the properties of currently used techniques with O(N log N) construction time for kd-trees and bounding volume hierarchies. Further, we will propose a hybrid data structure blending a spatial kd-tree with bounding volume primitives. We will keep our novel hierarchical data structures algorithmically efficient and comparable with kd-trees by using a cost model based on surface area heuristics. Although the time complexity O(N log N) is a lower bound required for construction of any spatial hierarchy that corresponds to sorting based on comparisons, using approximate method based on space discretization, we propose novel hierarchical data structures with an expected O(N log log N) time complexity. We will also discuss constants behind the construction algorithms of spatial hierarchies important in practice. We have documented the performance of our algorithms by results obtained from implementation on nine scenes.
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