A multiphase approach to efficient surface simplification

Garland,; Shaffer,

doi:10.1109/visual.2002.1183765

Cited by 36 publications

(27 citation statements)

References 13 publications

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“…These approaches are actually complementary: iterative edge contraction (based on quadratic error metrics, see [10], ( [11]), compared to vertex clustering approaches, leads to results of good quality but proves very costly both in terms of time and space. Vertex clustering algorithms (see for instance [20], [7], [17]) are simple, light and efficient methods but they hardly take into account the local geometry of the surface.…”

Section: Surface Mesh Segmentationmentioning

confidence: 99%

“…While n < m: In order to determine a subdivision plane appropriate to the repartition of vertices in the cell (see [11]), we use a principal component analysis of the normals of the cell (see [13]). …”

Section: Discrete Curvaturesmentioning

confidence: 99%

“…Observe that the sharp edges are well preserved. For geological surfaces, it is essential as In order to estimate the quality of our results, we have first compared them with those obtained by Shaffer and Garland with their mixed approach ( [11]). The tests have been performed with two models: the "lucky lady" model (500k vertices) and the "dragon" model (437k vertices).…”

Section: Discrete Curvaturesmentioning

confidence: 99%

See 2 more Smart Citations

Application of discrete curvatures to surface mesh simplification and feature line extraction

Bac

Mari

Kudelski

et al. 2014

Actes Des Rencontres Du CIRM

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Section: Surface Mesh Segmentationmentioning

confidence: 99%

Section: Discrete Curvaturesmentioning

confidence: 99%

Section: Discrete Curvaturesmentioning

confidence: 99%

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Application of discrete curvatures to surface mesh simplification and feature line extraction

Bac

Mari

Kudelski

et al. 2014

Actes Des Rencontres Du CIRM

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“…Garland and Shaffer in [17] present a technique that combines vertex clustering and iterative edge collapse. This approach works in two steps: the first step performs a uniform vertex clustering, as in the methods described above.…”

Section: Algorithms Based On Clusteringmentioning

confidence: 99%

“…Dataset Partitioning Simplification Multi-res Space Lindstrom [27] tri mesh regular grid vertex clustering NO O(out) Lindstrom et al [28] tri mesh regular grid vertex clustering NO O(1) Shaffer et al [40] tri mesh BSP tree vertex clustering NO O(out) Garland et al [17] …”

Section: Comparisonmentioning

confidence: 99%

Out-of-core Multiresolution Terrain Modeling

Danovaro

Floriani

Puppo

et al.

Spatial Data on the Web

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In this chapter we discuss issues about Level Of Detail (LOD) representations for digital terrain models and, especially, we describe how to deal with very large terrain datasets through out-of-core techniques that explicitly manage I/O operations between levels of memory. LOD modeling in the related context of geographical maps is discussed in Chapters 3 and 4.A dataset describing a terrain consists of a set of elevation measurements taken at a finite number of locations over a planar or a spherical domain. In a digital terrain model, elevation is extended to the whole domain of interest by averaging or interpolating the available measurements. Of course, the resulting model is affected by some approximation error and, in general, the higher the density of the samples, the smaller the error. The same arguments can be used for more general two-dimensional scalar, or vector fields (e.g., generated by simulation), defined over a manifold domain, and measured through some sampling process.Available terrain datasets are becoming larger and larger, and processing them at their full resolution often exhibits prohibitive computational costs, even for highend workstations. Simplification algorithms and multi-resolution models proposed in the literature may improve efficiency, by adapting resolution on-the-fly, according to the needs of a specific application [32]. Data at high resolution are preprocessed once in order to build a multi-resolution model, which can be queried on-line by the application. The multi-resolution model acts as a black box that provides simplified representations, where resolution is focused on the region of interest, and at the level of detail required by the application. A simplified representation is generally affected by some approximation error, which is usually associated with either the vertices, or the cells of the simplified mesh.Since current datasets often exceed the size of main memory, I/O operations between levels of memory are often the bottleneck in computation. A disk access is

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