Optimizing LBVH‐Construction and Hierarchy‐Traversal to accelerate kNN Queries on Point Clouds using the GPU

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dc.contributor.authorJakob, J.en_US
dc.contributor.authorGuthe, M.en_US
dc.contributor.editorBenes, Bedrich and Hauser, Helwigen_US
dc.date.accessioned2021-02-27T19:02:28Z
dc.date.available2021-02-27T19:02:28Z
dc.date.issued2021
dc.description.abstractProcessing point clouds often requires information about the point neighbourhood in order to extract, calculate and determine characteristics. We continue the tradition of developing increasingly faster neighbourhood query algorithms and present a highly efficient algorithm for solving the exact neighbourhood problem in point clouds using the GPU. Both, the required data structures and the NN query, are calculated entirely on the GPU. This enables real‐time performance for large queries in extremely large point clouds. Our experiments show a more than threefold acceleration, compared to state‐of‐the‐art GPU based methods including all memory transfers. In terms of pure query performance, we achieve over answered neighbourhood queries per millisecond for 16 nearest neighbours on common graphics hardware.en_US
dc.description.number1
dc.description.sectionheadersArticles
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume40
dc.identifier.doi10.1111/cgf.14177
dc.identifier.issn1467-8659
dc.identifier.pages124-137
dc.identifier.urihttps://doi.org/10.1111/cgf.14177
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14177
dc.publisher© 2021 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltden_US
dc.subjectnearest neighbour
dc.subjectradius queries
dc.subjectbounding volume hierarchies
dc.subjectbvh optimization
dc.subjectacceleration structures
dc.titleOptimizing LBVH‐Construction and Hierarchy‐Traversal to accelerate kNN Queries on Point Clouds using the GPUen_US
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