Multiresolution decimation based on global error

Ciampalini, Andrea; Cignoni, Paolo; Montani, Claudio; Scopigno, Roberto

doi:10.1007/s003710050101

Cited by 151 publications

(99 citation statements)

References 26 publications

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“…These meshes have been built with about the same number of vertices (1082 and 1083 vertices respectively). Figures 7e) and f) show the resulting segmentation of meshes in figures 7c) and 7d) when geometrical and image atributes are use in the similarity function (4), that is, the weights w I and w G has been set to 0.7 and 0.3, respectively. It can clearly be seen that segmentation obtained with the mesh produced with local error function (3) is quite better than the one obtained with the mesh produced with the local error (2), which takes into account the interpolation error.…”

Section: Resultsmentioning

confidence: 99%

“…In order to illustrate how geometrical atributes can improve the accuracy of mesh partition, figures 7g) and 7h) show the resulting segmentation when geometrical attributes are disregarded, that is, w I = 1.0 and w G = 0.0 in equation (4). Notice that geometrical attributes does not improve the segmentation for the mesh obtained taking into account interpolation errors (compare figures 7d) and 7h).…”

Section: Resultsmentioning

confidence: 99%

“…Many algorithms devoted to represent images by meshes are based on adaptive approaches [13,9,10,6]. Alternatively, some techniques have adopted an opposite strategy, i.e., a fine mesh is successively coarsened until the approximation error reaches a tolerance [4]. Mixed approaches that combine refinement and coarsening [15,14] as well as optimization for re-positioning the vertices in minimum error places have also been developed [19].…”

Section: Related Workmentioning

confidence: 99%

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Generating Segmented Quality Meshes from Images

et al. 2008

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Techniques devoted to generate a triangular mesh from images either take as starting point a segmented image or generate a mesh without distinguishing different structures contained in the image. The pre-segmentation and the absence of well defined structures may impose difficulties in using the resulting mesh in some applications, as for example numerical simulations. In this work we present a new technique for mesh generation that aims at eliminating the need for pre-processing by building the segmentation into the mesh generation process. Furthermore, the proposed technique generates theoretically guaranteed quality meshes, rendering our framework very appropriated for applications in numerical simulation as well as in image modeling. In fact, the effectiveness of our approach in both applications are presented and discussed.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Generating Segmented Quality Meshes from Images

et al. 2008

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“…The vase geometry was acquired with a Cyberware 3030 range scanner. The mesh obtained originally consisted of 2M faces, and it was simplified down to 20,000 faces using the Jade 2.0 simplification code [5] with an accuracy of 0.17 mm. The second object was a small Capodimonte statuette (around 25 cm.…”

Section: Evaluation Of Resultsmentioning

confidence: 99%

Acquiring, stitching and blending diffuse appearance attributes on 3D models

Rocchini¹,

Cignoni²,

Montani³

et al. 2002

Vis Comput

Self Cite

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A new system for the construction of highly realistic models of real free-form 3D objects is proposed, based on the integration of several techniques (automatic 3D scanning, inverse illumination, inverse texture-mapping and textured 3D graphics). Our system improves the quality of a 3D model (e.g. acquired with a range scanning device) by adding color detail and, if required, high frequency shape detail. Detail is obtained by processing a set of digital photographs of the object. This is carried out by performing several subtasks: to compute camera calibration and position, to remove illumination effects obtaining both illumination-invariant reflectance properties and a high resolution surface normal field, and finally to blend and stitch the acquired detail on the triangle mesh via standard texture mapping. In particular, the smooth join between different images that map on adjacent sections of the surface is obtained by applying an accurate piecewise local registration of the original images and by blending textures. For each mesh face which is on the adjacency border between different observed images, a corresponding triangular texture patch can also be resampled as a weighted blend of the corresponding adjacent image sections. Examples of the results obtained with sample works of art are presented and discussed.

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“…a two-manifold model) without topological changes. Among this set of techniques, those which allow the restoration of the initial geometry according to a geometric criterion (references [12], [13] for example) can be distinguished from those which do not explicitly use such a criterion (references [14], [15], [16], [17], [18] for example). Previous works have also led us to develop a simplification approach [19], [20] with specific shape preservation criteria.…”

Section: -20mentioning

confidence: 99%

Using Polyhedral Models to Automatically Sketch Idealized Geometry for Structural Analysis

Véron

Léon²

2001

Engineering with Computers

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is an open access repository that collects the work of Arts et Métiers ParisTech researchers and makes it freely available over the web where possible. applications, etc). Nevertheless, in the fields of structural analysis and computer visualization for example, several adaptations and idealizations of the initial geometry are often necessary. To this end, within this paper a new approach is proposed to simplify an initial manifold or non-manifold polyhedral model with respect to bounded errors specified by the user or set up, for example, from a preliminary F.E. analysis. The topological changes which may occur during a simplification because of the bounded error (or tolerance) values specified are performed using specific curvature and topological criteria and operators. Moreover, topological changes, whether they kept or not the manifold of the object are managed simultaneously with the geometric operations of the simplification process.

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Multiresolution decimation based on global error

Cited by 151 publications

References 26 publications

Generating Segmented Quality Meshes from Images

Generating Segmented Quality Meshes from Images

Acquiring, stitching and blending diffuse appearance attributes on 3D models

Using Polyhedral Models to Automatically Sketch Idealized Geometry for Structural Analysis

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