Robust Statistical Estimation of Curvature on Discretized Surfaces

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dc.contributor.authorKalogerakis, Evangelosen_US
dc.contributor.authorSimari, Patricioen_US
dc.contributor.authorNowrouzezahrai, Dereken_US
dc.contributor.authorSingh, Karanen_US
dc.contributor.editorAlexander Belyaev and Michael Garlanden_US
dc.date.accessioned2014-01-29T09:43:02Z
dc.date.available2014-01-29T09:43:02Z
dc.date.issued2007en_US
dc.description.abstractA robust statistics approach to curvature estimation on discretely sampled surfaces, namely polygon meshes and point clouds, is presented. The method exhibits accuracy, stability and consistency even for noisy, non-uniformly sampled surfaces with irregular configurations. Within an M-estimation framework, the algorithm is able to reject noise and structured outliers by sampling normal variations in an adaptively reweighted neighborhood around each point. The algorithm can be used to reliably derive higher order differential attributes and even correct noisy surface normals while preserving the fine features of the normal and curvature field. The approach is compared with state-of-the-art curvature estimation methods and shown to improve accuracy by up to an order of magnitude across ground truth test surfaces under varying tessellation densities and types as well as increasing degrees of noise. Finally, the benefits of a robust statistical estimation of curvature are illustrated by applying it to the popular applications of mesh segmentation and suggestive contour rendering.en_US
dc.description.seriesinformationGeometry Processingen_US
dc.identifier.isbn978-3-905673-46-3en_US
dc.identifier.issn1727-8384en_US
dc.identifier.urihttps://doi.org/10.2312/SGP/SGP07/013-022en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): I.3.5 [Computational Geometry and Object Modeling]: Geometric algorithms, languages, and systems; curve, surface, solid, and object representations.en_US
dc.titleRobust Statistical Estimation of Curvature on Discretized Surfacesen_US
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SGP07: Eurographics Symposium on Geometry Processing