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Proceedings of CAD'17, 2017, 332-336
Mesh Segmentation via Geodesic Curvature Flow

Stephen Baek, University of Iowa
Ramy Harik, University of South Carolina

Abstract. Segmentation of geometry data is one of the fundamental problems in computer-aided design and geometry modeling. The problem can be briefly stated as a task of finding a partition S of a geometry X. Mathematically, a partition S of a set X is a disjoint collection of nonempty and distinct subsets of X such that each member of X is a member of some, and hence, exactly one member of S. Intuitively, there can be more than one such a collection for a given X, and the problem of geometry data segmentation is, hence, to find the most perceptually sound partition of a given geometry X. Albeit ambiguous, the “perceptually sound” segmentation is, in general, defined based on a certain similarity metric depending on the application such that visually similar and contiguous members of   belong to the same subset of  S. In this regard, a large variety of computational methods has been proposed so far. Among those different approaches, one of the key challenges they share in common is how to define the similarity metric between the members of S.

Keywords. Geodesic Curvature Flow, Geometric Flow, Surface Metric, Shape Segmentation

DOI: 10.14733/cadconfP.2017.332-336