Recent Advances in Compression of 3D Meshes

Alliez, Pierre

doi:10.1007/3-540-26808-1_1

Cited by 194 publications

(151 citation statements)

References 51 publications

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“…One is the relationship between the triangle count reduction and geometry encoding [27], [28]. The scheme that we presented is not fully progressive, in the sense that the mesh has always the full connectivity.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Geometry-aware bases for shape approximation

Sorkine

Cohen–Or

Irony

et al. 2005

IEEE Trans. Visual. Comput. Graphics

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Abstract-We introduce a new class of shape approximation techniques for irregular triangular meshes. Our method approximates the geometry of the mesh using a linear combination of a small number of basis vectors. The basis vectors are functions of the mesh connectivity and of the mesh indices of a number of anchor vertices. There is a fundamental difference between the bases generated by our method and those generated by geometry-oblivious methods, such as Laplacian-based spectral methods. In the latter methods, the basis vectors are functions of the connectivity alone. The basis vectors of our method, in contrast, are geometry-aware, since they depend on both the connectivity and on a binary tagging of vertices that are "geometrically important" in the given mesh (e.g., extrema). We show that by defining the basis vectors to be the solutions of certain least-squares problems, the reconstruction problem reduces to solving a single sparse linear least-squares problem. We also show that this problem can be solved quickly using a state-of-the-art sparse-matrix factorization algorithm. We show how to select the anchor vertices to define a compact effective basis from which an approximated shape can be reconstructed. Furthermore, we develop an incremental update of the factorization of the least-squares system. This allows a progressive scheme where an initial approximation is incrementally refined by a stream of anchor points. We show that the incremental update and solving the factored system are fast enough to allow an on-line refinement of the mesh geometry.

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Section: Conclusion and Discussionmentioning

confidence: 99%

Geometry-aware bases for shape approximation

Sorkine

Cohen–Or

Irony

et al. 2005

IEEE Trans. Visual. Comput. Graphics

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“…Mesh compression is used to compactly store or transmit geometric models [4]. As with other data, compression rates are inversely proportional to the data entropy.…”

Section: Mesh Compressionmentioning

confidence: 99%

Mesh Parameterization Methods and Their Applications

Sheffer

Praun

Rose

2006

FNT in Computer Graphics and Vision

383

118

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We present a survey of recent methods for creating piecewise linear mappings between triangulations in 3D and simpler domains such as planar regions, simplicial complexes, and spheres. We also discuss emerging tools such as global parameterization, inter-surface mapping, and parameterization with constraints. We start by describing the wide range of applications where parameterization tools have been used in recent years. We then briefly review the pertinent mathematical background and terminology, before proceeding to survey the existing parameterization techniques. Our survey summarizes the main ideas of each technique and discusses its main properties, comparing it to other methods available. Thus it aims to provide guidance to researchers and developers when assessing the suitability of different methods for various applications. This survey focuses on the practical aspects of the methods available, such as time complexity and robustness and shows multiple examples of parameterizations generated using different methods, allowing the reader to visually evaluate and compare the results.

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“…Noise and incompleteness, however, make the process more difficult to achieve. While mesh compression is a mature field [5], there is still room for improvement in point cloud compression. To the best of our knowledge, present point-based compression strategies are mainly based on surface approximation [6,7], and/or hierarchical space subdivision by augmenting the dataset by a data structure (e.g.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Compression of Curve-Based Point Cloud

Daribo

Furukawa

Sagawa

et al. 2011

Advances in Image and Video Technology

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Abstract. With the increasing demands for highly detailed 3D data, dynamic scanning systems are capable of producing 3D+t (a.k.a. 4D) spatio-temporal models with millions of points recently. As a consequence, effective 4D geometry compression schemes are required to face the need to store/transmit the huge amount of data, in addition to classical static 3D data. In this paper, we propose a 4D spatio-temporal point cloud encoder via a curve-based representation of the point cloud, particularly well-suited for dynamic structured-light-based scanning systems, wherein a grid pattern is projected onto the surface object. The object surface is then naturally sampled in a series of curves, due to the grid pattern. This motivates our choice to leverage a curve-based representation to remove the spatial and temporal correlation of the sampled point along the scanning directions through a competitive-based predictive encoder that includes different spatio-temporal prediction modes. Experimental results show the significant gain obtained with the proposed method.

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Recent Advances in Compression of 3D Meshes

Cited by 194 publications

References 51 publications

Geometry-aware bases for shape approximation

Geometry-aware bases for shape approximation

Mesh Parameterization Methods and Their Applications

Dynamic Compression of Curve-Based Point Cloud

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