Moebius Transformations For Global Intrinsic Symmetry Analysis

dc.contributor.authorVladimir G. Kimen_US
dc.contributor.authorYaron Lipmanen_US
dc.contributor.authorXiaobai Chenen_US
dc.contributor.authorThomas Funkhouseren_US
dc.date.accessioned2015-02-23T17:15:42Z
dc.date.available2015-02-23T17:15:42Z
dc.date.issued2010en_US
dc.description.abstractThe goal of our work is to develop an algorithm for automatic and robust detection of global intrinsic symmetries in 3D surface meshes. Our approach is based on two core observations. First, symmetry invariant point sets can be detected robustly using critical points of the Average Geodesic Distance (AGD) function. Second, intrinsic symmetries are self-isometries of surfaces and as such are contained in the low dimensional group of Moebius transformations. Based on these observations, we propose an algorithm that: 1) generates a set of symmetric points by detecting critical points of the AGD function, 2) enumerates small subsets of those feature points to generate candidate Moebius transformations,and 3) selects among those candidate Moebius transformations the one(s) that best map the surface onto itself. The main advantages of this algorithm stem from the stability of the AGD in predicting potential symmetric point features and the low dimensionality of the Moebius group for enumerating potential self-mappings. During experiments with a benchmark set of meshes augmented with human-specified symmetric correspondences, we find that the algorithm is able to find intrinsic symmetries for a wide variety of object types with moderate deviations from perfect symmetry.en_US
dc.description.number5en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.identifier.doi10.1111/j.1467-8659.2010.01778.xen_US
dc.identifier.pages1689-1700en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/CGF.v29i5pp1689-1700en_US
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/CGF.v29i5pp1689-1700
dc.titleMoebius Transformations For Global Intrinsic Symmetry Analysisen_US
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