Exoskeleton: Curve network abstraction for 3D shapes

Goes, Fernando de; Goldenstein, Siome; Desbrun, Mathieu; Velho, Luiz

doi:10.1016/j.cag.2010.11.012

Cited by 33 publications

(18 citation statements)

References 48 publications

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“…In [10], we investigated the problem of abstracting 3D surfaces as a network of curves and presented a principled framework that combines structural segmentation and shape approximation.…”

Section: Simplificationmentioning

confidence: 99%

An Optimal Transport Approach to Robust Reconstruction and Simplification of 2D Shapes

Goes

Cohen-Steiner

Alliez

et al. 2011

Computer Graphics Forum

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We propose a robust 2D shape reconstruction and simplification algorithm which takes as input a defect‐laden point set with noise and outliers. We introduce an optimal‐transport driven approach where the input point set, considered as a sum of Dirac measures, is approximated by a simplicial complex considered as a sum of uniform measures on 0‐ and 1‐simplices. A fine‐to‐coarse scheme is devised to construct the resulting simplicial complex through greedy decimation of a Delaunay triangulation of the input point set. Our method performs well on a variety of examples ranging from line drawings to grayscale images, with or without noise, features, and boundaries.

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“…In [10], we investigated the problem of abstracting 3D surfaces as a network of curves and presented a principled framework that combines structural segmentation and shape approximation.…”

Section: Simplificationmentioning

confidence: 99%

An Optimal Transport Approach to Robust Reconstruction and Simplification of 2D Shapes

Goes

Cohen-Steiner

Alliez

et al. 2011

Computer Graphics Forum

Self Cite

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“…Therefore, few works apply these two types simultaneously. Goes et al [2] introduced an abstraction that conveys both the perceptual and the geometric structure. But it only gets abstraction of shapes.…”

Section: Introductionmentioning

confidence: 99%

Shape segmentation by hierarchical splat clustering

Zhang

Gao

et al. 2015

Computers & Graphics

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“…Recently, there has been work on shape abstraction using curve networks [Mehra et al 2009;de Goes et al 2011]. These methods and their variants evaluate the quality of an approximation by the geometric deviation of the proxy from the original shape.…”

Section: Introductionmentioning

confidence: 99%

Slices

2011

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selection of user study models with user prescribed slices input mesh computed planar slices geometric features with associated planes slicing result on a model not in the training set physical paper puppet Figure 1: Based on a user study, where participants abstracted meshes of common objects using a small collection of planar slices, we develop an automatic algorithm to create planar slice based abstractions of (untrained) models. Starting from a set of planar slices, approximating the object's geometric features, the algorithm picks a subset of planes based on relative feature importance learned from the user study. AbstractMinimalist object representations or shape-proxies that spark and inspire human perception of shape remain an incompletely understood, yet powerful aspect of visual communication. We explore the use of planar sections, i.e., the contours of intersection of planes with a 3D object, for creating shape abstractions, motivated by their popularity in art and engineering. We first perform a user study to show that humans do define consistent and similar planar section proxies for common objects. Interestingly, we observe a strong correlation between user-defined planes and geometric features of objects. Further we show that the problem of finding the minimum set of planes that capture a set of 3D geometric shape features is both NP-hard and not always the proxy a user would pick. Guided by the principles inferred from our user study, we present an algorithm that progressively selects planes to maximize feature coverage, which in turn influence the selection of subsequent planes. The algorithmic framework easily incorporates various shape features, while their relative importance values are computed and validated from the user study data. We use our algorithm to compute planar slices for various objects, validate their utility towards object abstraction using a second user study, and conclude showing the potential applications of the extracted planar slice shape proxies.

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Exoskeleton: Curve network abstraction for 3D shapes

Cited by 33 publications

References 48 publications

An Optimal Transport Approach to Robust Reconstruction and Simplification of 2D Shapes

An Optimal Transport Approach to Robust Reconstruction and Simplification of 2D Shapes

Shape segmentation by hierarchical splat clustering

Slices

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