User-assisted simplification method for triangle meshes preserving boundaries

Gonzalez, C. Diez; Gumbau, Jesús; Chover, Miguel; Ramos, Francisco; Quirós, Ricardo

doi:10.1016/j.cad.2009.09.007

Cited by 14 publications

(10 citation statements)

References 25 publications

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“…We have evaluated our approach on four different scenes (see Table 1), by running our decimation algorithm on an Intel Xeon E5-2609 1.90GHz, 16BG of RAM. We implemented standard QEM [3], boundary-aware decimation [31] and our approach in C++ without optimization. All our timings are based on these homogeneously non-optimal implementations to provide fairer comparisons.…”

Section: Resultsmentioning

confidence: 99%

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Proximity-aware multiple meshes decimation using quadric error metric

et al. 2020

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Progressive mesh decimation by successive edge collapses is a standard tool in geometry processing. A key element of such algorithms is the error metric, which prioritizes the edge collapses to greedily minimize the simplification error. Most previous works focus on preserving local shape properties. However, meshes describing complex systems often require significant decimation for fast transmission and visualization on low-end terminals, and preserving the arrangement of objects is required to maintain the overall system readability for applications such as on-site repair, inspection, training, serious games, etc. We present a novel approach for the joint decimation of multiple triangular meshes. We combine local edge error (e.g. Quadric Error Metric) with a proximity-aware penalty function, which increases the error of edge collapses modifying the geometry in proximity areas. We propose an automatic detection of proximity areas and we demonstrate the performances of our approach on several models generated from CAD scenes. 3 interacting with such data remains very challenging, as the data 4 complexity and scale stress both hardware and software com-5 ponents in real-life applications. This becomes even more criti-6 cal with mobile platforms and web-embedded 3D visualization, 7 which require fast 3D data transfer and rendering even on low 8 end terminals. Despite their limited performances, mobile plat-9 forms are very attractive as they bring access to rich information 10 on-site, and help users performing tasks in complex environ-11 ments (e.g. machinery maintenance). The relatively low cost 12 and ubiquity of mobile devices also make them very attractive 13 as support for teaching and training. 14 To mitigate the increasing complexity of 3D datasets for 15 low-performance hardware, a common solution is to reduce 16 the polygon count of large 3D meshes using decimation algo-17 rithms [1]. In order to keep the decimation algorithms tractable, 18 the preservation of the mesh properties (e.g. parameterization

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Section: Resultsmentioning

confidence: 99%

“…We also compare our approach to González et al [31], who are collapsed with halfedge collapse rather than edge collapse.…”

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confidence: 99%

Proximity-aware multiple meshes decimation using quadric error metric

et al. 2020

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“…is convergence speed is lower than that in the vertex decimation and vertex clustering methods. us, maintaining a trade-off between time efficiency and salient feature preservation for the current mesh simplification methods continues to be a challenge [31].…”

Section: Related Workmentioning

confidence: 99%

Fast Mesh Simplification Method for Three-Dimensional Geometric Models with Feature-Preserving Efficiency

Wang

Zheng

Wang

2019

Scientific Programming

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To avoid excessive details, thus omitting less important content, of three-dimensional (3D) geometric models, this study proposes a fast mesh simplification method based on an energy-operator for 3D geometric models with salient feature-preserving efficiency. The energy-operator can evaluate the smoothness and complexity of the regional mesh in 3D models. Accordingly, it can be directly used to simultaneously reduce the candidate triangle and its three neighboring triangles. The proposed method can dramatically collapse the excessive details in relatively smooth areas and preserve more important salient features during the simplification process. It can also maintain a trade-off between time efficiency and salient feature-preserving accuracy. The effectiveness and efficiency of the new method are demonstrated by comparing it with OpenMesh, which is considered the most popular mesh operation software and is capable of achieving accurate mesh simplification models. The new mesh simplification method based on the energy-operator can provide accurate and concise models for interactive 3D rendering, calculating, simulating, and analyzing.

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“…Figure 3 depicts the compressed horse model constructed with several basis functions from the original mesh. Mesh Simplification (Gonzalez, Gumbau, Chover, Ramos, & Quiros, 2009) may also be used to transform a 3D model to a new mesh with smaller number of faces, edges and verti-ces. The simplification procedure is regularly restricted by a set of quality criteria that can protect specific properties of the original model as much as possible (Gotsman, Gumhold, & Kobbelt, 1998).…”

Section: Robustness Against 3d Attacksmentioning

confidence: 99%

Spectral Graph and Minimal Spanning Tree for 3D Polygonal Meshes Fingerprinting

Abdallah

Al‐Oqily

Abdallah

et al. 2014

International Journal of Information Technology and Web Engineering

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In this paper, the authors present a robust three-dimensional fingerprint algorithm for verification, indexing, and identification. The core idea behind our technique is to apply the eigen-decomposition to the mesh Laplacian matrix, and then compute minimum spanning trees (MST) of several concentrations of the mesh shape structure. The fixed size hash vector of a 3D mesh is defined in terms of the MST values and number of the initial patches. The extensive experimental results on several 3D meshes prove the uniqueness of the extracted hash vectors and the robustness of the proposed technique against the most common attacks including distortion-less attacks, compression, noise, smoothing, scaling, rotation as well as mixtures of these attacks.

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User-assisted simplification method for triangle meshes preserving boundaries

Cited by 14 publications

References 25 publications

Proximity-aware multiple meshes decimation using quadric error metric

Proximity-aware multiple meshes decimation using quadric error metric

Fast Mesh Simplification Method for Three-Dimensional Geometric Models with Feature-Preserving Efficiency

Spectral Graph and Minimal Spanning Tree for 3D Polygonal Meshes Fingerprinting

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