Surfel Based Geometry Resonstruction

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    We propose a method for retrieving a piecewise smooth surface from noisy data. In data acquired by a scanning process sampled points are almost never on the discontinuities making reconstruction of surfaces with sharp features difficult. Our method is based on a Markov Random Field (MRF) formulation of a surface prior, with the surface represented as a collection of small planar patches, the surfels, associated with each data point. The main advantage of using surfels is that we avoid treating data points as vertices. MRF formulation of the surface prior allows us to separately model the likelihood (related to the mesh formation process) and the local surface properties. We chose to model the smoothness by considering two terms: the parallelism between neighboring surfels, and their overlap. We have demonstrated the feasibility of this approach on both synthetical and scanned data. In both cases sharp features were precisely located and planar regions smoothed.
    Original languageEnglish
    Title of host publicationTheory and Practice of Computer Graphics 2010 : Eurographics UK Chapter Proceedings
    EditorsJohn Collomosse, Ian Grimstead
    PublisherEurographics Association
    Publication date2010
    ISBN (Print)978-3-905673-75-3
    Publication statusPublished - 2010
    EventTheory and Practice of Computer Graphics - Sheffield, United Kingdom
    Duration: 6 Sep 20108 Sep 2010
    Conference number: 8


    ConferenceTheory and Practice of Computer Graphics
    CountryUnited Kingdom

    Cite this

    Andersen, V., Aanæs, H., & Bærentzen, J. A. (2010). Surfel Based Geometry Resonstruction. In J. Collomosse, & I. Grimstead (Eds.), Theory and Practice of Computer Graphics 2010: Eurographics UK Chapter Proceedings (pp. 39-44). Eurographics Association.