Efficient Image-Based Proximity Queries with Object-Space Precision
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Date
2012
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Publisher
The Eurographics Association and Blackwell Publishing Ltd.
Abstract
We present an efficient algorithm for object-space proximity queries between multiple deformable triangular meshes. Our approach uses the rasterization capabilities of the GPU to produce an image-space representation of the vertices. Using this image-space representation, inter-object vertex-triangle distances and closest points lying under a user-defined threshold are computed in parallel by conservative rasterization of bounding primitives and sorted using atomic operations. We additionally introduce a similar technique to detect penetrating vertices. We show how mechanisms of modern GPUs such as mipmapping, Early-Z and Early-Stencil culling can optimize the performance of our method. Our algorithm is able to compute dense proximity information for complex scenes made of more than a hundred thousand triangles in real time, outperforming a CPU implementation based on bounding volume hierarchies by more than an order of magnitude.
Description
@article{10.1111:j.1467-8659.2011.02084.x,
journal = {Computer Graphics Forum},
title = {{Efficient Image-Based Proximity Queries with Object-Space Precision}},
author = {Morvan, T. and Reimers, M. and Samset, E.},
year = {2012},
publisher = {The Eurographics Association and Blackwell Publishing Ltd.},
ISSN = {1467-8659},
DOI = {10.1111/j.1467-8659.2011.02084.x}
}