Implicit Surface Reconstruction and Feature Detection with a Learning Algorithm

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dc.contributor.authorKaye, Daviden_US
dc.contributor.authorIvrissimtzis, Ionnisen_US
dc.contributor.editorJohn Collomosse and Ian Grimsteaden_US
dc.date.accessioned2014-01-31T20:11:55Z
dc.date.available2014-01-31T20:11:55Z
dc.date.issued2010en_US
dc.description.abstractWe propose a new algorithm for implicit surface reconstruction and feature detection. The algorithm is based on a self organising map with the connectivity of a regular 3D grid that can be trained into an implicit representation of surface data. The implemented self organising map stores not only its current state but also its recent training history which can be used for feature detection. Preliminary results show that the proposed algorithm gives good quality reconstructions and can detect various types of feature.en_US
dc.description.seriesinformationTheory and Practice of Computer Graphicsen_US
dc.identifier.isbn978-3-905673-75-3en_US
dc.identifier.urihttps://doi.org/10.2312/LocalChapterEvents/TPCG/TPCG10/127-130en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling I.6.5 [Simulation and modeling]: Model Developmenten_US
dc.titleImplicit Surface Reconstruction and Feature Detection with a Learning Algorithmen_US
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