High Performance GPU‐based Proximity Queries using Distance Fields
Identifieur interne : 005068 ( Main/Merge ); précédent : 005067; suivant : 005069High Performance GPU‐based Proximity Queries using Distance Fields
Auteurs : T. Morvan [Norvège] ; M. Reimers [Norvège] ; E. Samset [Norvège]Source :
- Computer Graphics Forum [ 0167-7055 ] ; 2008-12.
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Abstract
Proximity queries such as closest point computation and collision detection have many applications in computer graphics, including computer animation, physics‐based modelling, augmented and virtual reality. We present efficient algorithms for proximity queries between a closed rigid object and an arbitrary, possibly deformable, polygonal mesh. Using graphics hardware to densely sample the distance field of the rigid object over the arbitrary mesh, we compute minimal proximity and collision response information on the graphics processing unit (GPU) using blending and depth buffering, as well as parallel reduction techniques, thus minimizing the readback bottleneck. Although limited to image‐space resolution, our algorithm provides high and steady performance when compared with other similar algorithms. Proximity queries between arbitrary meshes with hundreds of thousands of triangles and detailed distance fields of rigid objects are computed in a few milliseconds at high‐sampling resolution, even in situations with large overlap.
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DOI: 10.1111/j.1467-8659.2008.01183.x
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<front><div type="abstract" xml:lang="en">Proximity queries such as closest point computation and collision detection have many applications in computer graphics, including computer animation, physics‐based modelling, augmented and virtual reality. We present efficient algorithms for proximity queries between a closed rigid object and an arbitrary, possibly deformable, polygonal mesh. Using graphics hardware to densely sample the distance field of the rigid object over the arbitrary mesh, we compute minimal proximity and collision response information on the graphics processing unit (GPU) using blending and depth buffering, as well as parallel reduction techniques, thus minimizing the readback bottleneck. Although limited to image‐space resolution, our algorithm provides high and steady performance when compared with other similar algorithms. Proximity queries between arbitrary meshes with hundreds of thousands of triangles and detailed distance fields of rigid objects are computed in a few milliseconds at high‐sampling resolution, even in situations with large overlap.</div>
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