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dc.contributor.authorAlgorri, Maria-Elenaen_US
dc.contributor.authorSchmitt, Francisen_US
dc.date.accessioned2014-10-21T07:41:34Z
dc.date.available2014-10-21T07:41:34Z
dc.date.issued1996en_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttp://dx.doi.org/10.1111/1467-8659.1510047en_US
dc.description.abstractBuilding 3 0 models from unstructured data is a problem that arises increasingly as new 30 scanning technology is able to produce large and complex databases of full 3 0 information. Huge efforts put into segmenting entire sets of 20 images demand robust tools that are then able to reconstruct any arbitrary 30 surface segmented from the images. In this paper we propose an algorithmic methodology that automatically produces a surface from a set of points in ?3 about which we have no topological knowledge. Our method uses a spatial decomposition and a surface tracking algorithm to produce a rough approximation S of the unknown manifold S. The produced surface S serves as a robust initialisation for a physically based modeling technique that yields the fine details of S and so improves the quality of the reconstruction.en_US
dc.publisherBlackwell Science Ltd and the Eurographics Associationen_US
dc.titleSurface Reconstruction from Unstructured 3D Dataen_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume15en_US
dc.description.number1en_US
dc.identifier.doi10.1111/1467-8659.1510047en_US
dc.identifier.pages47-60en_US


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