CSDL Home IEEE Transactions on Visualization & Computer Graphics 2009 vol.15 Issue No.06 - November/December

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Issue No.06 - November/December (2009 vol.15)

pp: 1201-1208

Gregory Cipriano , University of Wisconsin

George N. Phillips Jr. , University of Wisconsin

Michael Gleicher , University of Wisconsin

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TVCG.2009.168

ABSTRACT

Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis.

INDEX TERMS

Curvature, descriptors, npr, stylized rendering, shape matching.

CITATION

Gregory Cipriano, George N. Phillips Jr., Michael Gleicher, "Multi-Scale Surface Descriptors",

*IEEE Transactions on Visualization & Computer Graphics*, vol.15, no. 6, pp. 1201-1208, November/December 2009, doi:10.1109/TVCG.2009.168REFERENCES