An Unified Multiscale Framework for Planar, Surface, and Curve Skeletonization

Jalba, Andrei C.; Sobiecki, André; Telea, Alexandru

doi:10.1109/tpami.2015.2414420

Cited by 40 publications

(53 citation statements)

References 68 publications

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“…Similarly, Au et al [2008] and Zheng et al [2011] extract GCs by examining thicknesses about extracted curve skeletons and find cuts based on concavity and length of cut boundaries. Other multi-scale skeleton extraction methods include [Miklos et al 2010] and [Jalba et al 2015].…”

Section: Skeleton-based Segmentationmentioning

confidence: 99%

Generalized cylinder decomposition

Zhou¹,

Yin²,

Huang³

et al. 2015

ACM Trans. Graph.

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Decomposing a complex shape into geometrically simple primitives is a fundamental problem in geometry processing. We are interested in a shape decomposition problem where the simple primitives sought are generalized cylinders, which are ubiquitous in both organic forms and man-made artifacts. We introduce a quantitative measure of cylindricity for a shape part and develop a cylindricitydriven optimization algorithm, with a global objective function, for generalized cylinder decomposition. As a measure of geometric simplicity and following the minimum description length principle, cylindricity is defined as the cost of representing a cylinder through skeletal and cross-section profile curves. Our decomposition algorithm progressively builds local to non-local cylinders, which form over-complete covers of the input shape. The over-completeness of the cylinder covers ensures a conservative buildup of the cylindrical parts, leaving the final decision on decomposition to global optimization. We solve the global optimization by finding an exact cover, which optimizes the global objective function. We demonstrate results of our optimal decomposition algorithm on numerous examples and compare with other alternatives.

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Section: Skeleton-based Segmentationmentioning

confidence: 99%

Generalized cylinder decomposition

Zhou¹,

Yin²,

Huang³

et al. 2015

ACM Trans. Graph.

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show abstract

“…These are commonly categorised based upon their input, which can be a surface mesh [11,12], a point cloud [13,14] or a voxel grid [15,16]. Volumetric representations, while important, are not handled by our tool, hence they will be not discussed.…”

Section: Related Workmentioning

confidence: 99%

An interactive editor for curve-skeletons: SkeletonLab

Barbieri

Meloni

Usai

et al. 2016

Computers & Graphics

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Curve-skeletons are powerful shape descriptors able to provide higher level information on topology, structure and semantics of a given digital object. Their range of application is wide and encompasses computer animation, shape matching, modelling and remeshing. While a universally accepted definition of curve-skeleton is still lacking, there are currently many algorithms for the curve-skeleton computation (or skeletonization) as well as different techniques for building a mesh around a given curve-skeleton (inverse skeletonization). Despite their widespread use, automatically extracted skeletons usually need to be processed in order to be used in further stages of any pipeline, due to different requirements. We present here an advanced tool, named SkeletonLab, that provides simple interactive techniques to rapidly and automatically edit and repair curve skeletons generated using different techniques proposed in literature, as well as handcrafting them. The aim of the tool is to allow trained practitioners to manipulate the curve-skeletons obtained with skeletonization algorithms in order to fit their specific pipelines or to explore the requirements of newly developed techniques.

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“…A similar segmentation method, using high-resolution point-cloud skeletons computed on the GPU [17] along the method of Reniers et al [40], is proposed in [22]. Similar high-resolution surface and curve skeletons can be computed in voxel space using an advection model [18]. However, such skeletons have not yet been used for segmentation purposes.…”

Section: Related Workmentioning

confidence: 99%

“…For this, we tested the methods in [40] and [18]. As also described in [18], both methods produce very similar medial surfaces, and also deliver a skeleton importance metric, required to simplify skeletons to e.g. eliminate noise or small details.…”

Section: Implementationmentioning

confidence: 99%

See 1 more Smart Citation

Improved Part-Based Segmentation of Voxel Shapes by Skeleton Cut Spaces

Feng

Jalba

Telea

2016

Mathematical Morphology - Theory and Applications

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Abstract:We present a re ned method for part-based segmentation of voxel shapes by constructing partitioning cuts from every voxel of the shape's medial surface. Our cuts have several desirable propertiessmoothness, tightness, and orientation with respect to the shape's local symmetry axis, making it a good segmentation tool. We analyze the space of all cuts created for a given shape and detect cuts which are good segment borders. We present a detailed analysis of the parameter space of our method, which yields good preset values for all its parameters. Our method is robust to noise, pose invariant, independent on the shape geometry and genus, and is simple to implement. We demonstrate our method for both automatic and interactive segmentation on a wide selection of 3D shapes.

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An Unified Multiscale Framework for Planar, Surface, and Curve Skeletonization

Cited by 40 publications

References 68 publications

Generalized cylinder decomposition

Generalized cylinder decomposition

An interactive editor for curve-skeletons: SkeletonLab

Improved Part-Based Segmentation of Voxel Shapes by Skeleton Cut Spaces

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