Friston, SJ;
Steed, A;
(2019)
Real-Time Collision Detection for Deformable Characters with Radial Fields.
IEEE Transactions on Visualization and Computer Graphics
, 25
(8)
pp. 2611-2622.
10.1109/TVCG.2018.2859924.
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Abstract
Many techniques facilitate real-time collision detection against complex models. These typically work by pre-computing information about the spatial distribution of geometry into a form that can be quickly queried. When models deform though, expensive pre-computations are impractical. We present radial fields: a variant of distance fields parameterised in cylindrical space, rather than Cartesian space. This 2D parameterisation significantly reduces the memory and computation requirements of the field, while introducing minimal overhead in collision detection tests. The interior of the mesh is defined implicitly for the entire domain. Importantly, it maps well to the hardware rasteriser of the GPU. Radial fields are much more application-specific than traditional distance fields. For these applications - such as collision detection with articulated characters - however, the benefits are substantial.
Type: | Article |
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Title: | Real-Time Collision Detection for Deformable Characters with Radial Fields |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/TVCG.2018.2859924 |
Publisher version: | http://dx.doi.org/10.1109/TVCG.2018.2859924 |
Language: | English |
Additional information: | This work is licensed under a Creative Commons Attribution 3.0 License. For more information, see http://creativecommons.org/licenses/by/3.0/. |
Keywords: | Collision avoidance, Geometry, Real-time systems, Deformable models, Graphics processing units, Computational modeling, Acceleration, distance fields, collision detection, deformable meshes, articulated characters |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/10054114 |
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