Mesh Segmentation - A Comparative Study

Attene, Marco; Katz, Shmuel; Mortara, Michela; Patanè, Giuseppe; Spagnuolo, Michela; Tal, Ayellet

doi:10.1109/smi.2006.24

Cited by 195 publications

(147 citation statements)

References 34 publications

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“…Many mesh segmentation methods exist in the graphics literature that aim to decompose a mesh into functional parts; a recent survey can be found in [28] and [1], and comparisons between several algorithms appear in [3]. These b) Consistent Segmentation a) Individual Segmentations Figure 1: Individual segmentations of a set of chairs are shown in (a).…”

Section: Previous Workmentioning

confidence: 99%

Consistent segmentation of 3D models

Golovinskiy

Funkhouser

2009

Computers & Graphics

174

149

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This paper proposes a method to segment a set of models consistently. The method simultaneously segments models and creates correspondences between segments. First, a graph is constructed whose nodes represent the faces of every mesh, and whose edges connect adjacent faces within a mesh and corresponding faces in different meshes. Second, a consistent segmentation is created by clustering this graph, allowing for outlier segments that are not present in every mesh. The method is demonstrated for several classes of objects and used for two applications: symmetric segmentation and segmentation transfer.

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Section: Previous Workmentioning

confidence: 99%

Consistent segmentation of 3D models

Golovinskiy

Funkhouser

2009

Computers & Graphics

174

149

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“…However, it is most closely related to shape segmentation methods, in particular pose invariant segmentations. Recent overviews on segmentation algorithms can be found in [4] and [5].…”

Section: Related Workmentioning

confidence: 99%

Hierarchical Shape Segmentation and Registration via Topological Features of Laplace-Beltrami Eigenfunctions

Reuter

2009

Int J Comput Vis

152

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This work introduces a method to hierarchically segment articulated shapes into meaningful parts and to register these parts across populations of nearisometric shapes (e.g. head, arms, legs and fingers of humans in different body postures). The method exploits the isometry invariance of eigenfunctions of the Laplace-Beltrami operator and uses topological features (level sets at important saddles) for the segmentation. Concepts from persistent homology are employed for a hierarchical representation, for the elimination of topological noise and for the comparison of eigenfunctions. The obtained parts can be registered via their spectral embedding across a population of near isometric shapes. This work also presents the highly accurate computation of eigenfunctions and eigenvalues with cubic finite elements on triangle meshes and discusses the construction of persistence diagrams from the MorseSmale complex as well as the relation to size functions.

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“…We refer readers to excellent surveys [11,12] for more in-depth discussions of these and other works. Segmentation methods generally fall into two camps, being either part-based or patch-based.…”

Section: Surface Segmentationmentioning

confidence: 99%

Feature-aligned segmentation using correlation clustering

et al. 2017

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We present an algorithm for segmenting a mesh into patches whose boundaries are aligned with prominent ridge and valley lines of the shape. Our key insight is that this problem can be formulated as correlation clustering (CC), a graph partitioning problem originating from the data mining community. The formulation lends two unique advantages to our method over existing segmentation methods. First, since CC is non-parametric, our method has few parameters to tune. Second, as CC is governed by edge weights in the graph, our method offers users direct and local control over the segmentation result. Our technical contributions include the construction of the weighted graph on which CC is defined, a strategy for rapidly computing CC on this graph, and an interactive tool for editing the segmentation. Our experiments show that our method produces qualitatively better segmentations than existing methods on a wide range of inputs.

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Mesh Segmentation - A Comparative Study

Abstract: Abstract

Cited by 195 publications

References 34 publications

Consistent segmentation of 3D models

Consistent segmentation of 3D models

Hierarchical Shape Segmentation and Registration via Topological Features of Laplace-Beltrami Eigenfunctions

Feature-aligned segmentation using correlation clustering

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