IEEE Trans Vis Comput Graph - Exact and Adaptive Signed Distance Fields Computation for Rigid and Deformable Models on GPUs.

Tópicos

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Resumo

Most techniques for real-time construction of a signed distance field, whether on a CPU or GPU, involve approximate distances. We use a GPU to build an exact adaptive distance field, constructed from an octree by using the Morton code. We use rectangle-swept spheres to construct a bounding volume hierarchy (BVH) around a triangulated model. To speed up BVH construction, we can use a multi-BVH structure to improve the workload balance between GPU processors. An upper bound on distance to the model provided by the octree itself allows us to reduce the number of BVHs involved in determining the distances from the centers of octree nodes at successively lower levels, prior to an exact distance query involving the remaining BVHs. Distance fields can be constructed 35-64 times as fast as a serial CPU implementation of a similar algorithm, allowing us to simulate a piece of fabric interacting with the Stanford Bunny at 20 frames per second.

Resumo Limpo

techniqu realtim construct sign distanc field whether cpu gpu involv approxim distanc use gpu build exact adapt distanc field construct octre use morton code use rectangleswept sphere construct bound volum hierarchi bvh around triangul model speed bvh construct can use multibvh structur improv workload balanc gpu processor upper bound distanc model provid octre allow us reduc number bvhs involv determin distanc center octre node success lower level prior exact distanc queri involv remain bvhs distanc field can construct time fast serial cpu implement similar algorithm allow us simul piec fabric interact stanford bunni frame per second

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