Triangle Influence Supersets for Fast Distance Computation

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dc.contributor.authorPujol, Eduarden_US
dc.contributor.authorChica, Antonioen_US
dc.contributor.editorHauser, Helwig and Alliez, Pierreen_US
dc.date.accessioned2023-10-06T11:58:55Z
dc.date.available2023-10-06T11:58:55Z
dc.date.issued2023
dc.description.abstractWe present an acceleration structure to efficiently query the Signed Distance Field (SDF) of volumes represented by triangle meshes. The method is based on a discretization of space. In each node, we store the triangles defining the SDF behaviour in that region. Consequently, we reduce the cost of the nearest triangle search, prioritizing query performance, while avoiding approximations of the field. We propose a method to conservatively compute the set of triangles influencing each node. Given a node, each triangle defines a region of space such that all points inside it are closer to a point in the node than the triangle is. This property is used to build the SDF acceleration structure. We do not need to explicitly compute these regions, which is crucial to the performance of our approach. We prove the correctness of the proposed method and compare it to similar approaches, confirming that our method produces faster query times than other exact methods.en_US
dc.description.number6
dc.description.sectionheadersORIGINAL ARTICLES
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14861
dc.identifier.issn1467-8659
dc.identifier.urihttps://doi.org/10.1111/cgf.14861
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14861
dc.publisher© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectdistance fields
dc.subjectimplicit surfaces
dc.subjectmodelling
dc.titleTriangle Influence Supersets for Fast Distance Computationen_US
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