A survey on Mesh Segmentation Techniques

By Ariel Shamir. Computer graphics forum (Print), 2008

679 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design

View Paper: https://www.semanticscholar.org/paper/5a8fd76f30f1487d3bb48d7174a911353cdfc523

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In Computational Mechanics

In Computer Graphics and Computer-Aided Design

Citations in the corpus

Synthetic Data for Deep Learning (2019, background): “, breaking an airplane into wings, body, and tail) is a manual process even in a synthetic dataset, while shape segmentation models increasingly rely on synthetic data [670]; this also relates to the 3D mesh segmentation problem [541].”
Contextual Part Analogies in 3D Objects (2010, background): “For a survey on different mesh partitioning techniques we refer the reader to (Shamir 2007).”
A Part‐aware Surface Metric for Shape Analysis (2009, background): “A classical application of surface metrics is mesh segmentation [Sha08].”
PointGrid: A Deep Network for 3D Shape Understanding (2018, background): “), dihedral angles between triangles [58], curvatures (Gaussian curvature or mean curvature) [30], geodesic distances on a mesh [17, 64], slippage [61], symmetry, convexity, medial axis [33], shape diameter [44] and motion characteristics [43], shape contexts [4], spin images [21], etc.”
Data-driven contextual modeling for 3D scene understanding (2016, methodology): “Mesh segmentation is a fun98 damental shape analysis problem in computer graphics, 99 for which both heuristic methods [12] and data-driven 100 approach [13] have been extensively studied over the 101 years.”
Voronoi-Based Curvature and Feature Estimation from Point Clouds (2011, methodology): “As in the case of curvature and feature estimation, most existing methods rely on meshes (see [31] for a survey).”
Interactive shape co-segmentation via label propagation (2014, neutral): “Consequently, they have received significant attention [14].”
Joint shape segmentation with linear programming (2011, background): “Many shape processing and 3D modeling applications benefit from automatic segmentation of shapes into components that appear natural [Shamir 2008; Chen et al. 2009; Chaudhuri et al. 2011].”
Active co-analysis of a set of shapes (2012, methodology): “Learning methods use the knowledge present in sets of shapes to solve classical problems, such as shape segmentation [Shamir 2008; Chen et al. 2009].”
Unsupervised co-segmentation for 3D shapes using iterative multi-label optimization (2013, background): “It is well known that shape descriptors play an important role in analyzing the surface geometry and a classical application of surface descriptors is shape segmentation [8].”
Learning 3D Part Detection from Sparsely Labeled Data (2014, background): “The problem of mesh labeling has largely been approached via segmentation (see [20], [8], [10], [22]).”