Progressive geometry compression

By A. Khodakovsky, Peter Schröder, Wim Sweldens. International Conference on Computer Graphics and Interactive Techniques, 2000

676 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/2a75c53ddc3ad66a56e14bf1b77ffec41a040ef5

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In Computational Mechanics

In Computer Graphics and Computer-Aided Design

In Computer Vision and Pattern Recognition

Citations in the corpus

Recent Advances in Remeshing of Surfaces (2008, background): “The main idea behind these techniques [40, 30, 38, 60] is the observation that a mesh representation has three components: geometry, connectivity and parameterization, of which the latter two (i.”
Differential Representations for Mesh Processing (2006, methodology): “One possible approach of direct application of the signal processing theory on meshes is to first perform semi-regular remeshing by parameterizing the mesh over a simple base complex, and then apply variations of 2D signal processing methods [18,19,20,21,22].”
Multi-Chart Geometry Images (2003, background): “For these representations, special kinds of continuous multiresolution basis functions can be derived that allow multiresolution editing [Zorin et al. 1997] and compression [Khodakovsky et al. 2000].”
PSEUDO-SPLINES, WAVELETS AND FRAMELETS (2007, methodology): “In applications like image compression, the short Riesz wavelet system can be applied to obtain fast reconstruction algorithm, while the decomposition is obtained by solving a linear system of equations (see [39]).”
Discrete Differential Geometry (2008, methodology): “Differenzengeometrie. Berlin etc.: Springer, 1970, 234 pp. [ 5 ] A.I.”
Spectral compression of mesh geometry (2000, methodology): “As this paper went to press, we discovered that [ 12 ] addresses this issue.”
Normal Multiresolution Approximation of Curves (2004, background): “This is clearly extremely useful for compression applications, see [14, 13].”
Technologies for 3D mesh compression: A survey (2005, methodology): “It was shown by experiments that the spherical geometry image coder achieves better R-D performance than the square domain approach [76] and the wavelet mesh coder [70], but slightly worse performance than the normal mesh coder [74].”
Geometry images (2002, methodology): “[10] use the MAPS scheme [13] to partition the mesh into charts and create the chart parametrizations.”
Coding Algorithms for 3DTV—A Survey (2007, methodology): “the wavelet (WL)-based approach [80] of Khodakovsky et al.”
High-Pass Quantization for Mesh Encoding (2003, neutral): “Another possibility is to alter the surface representation; for instance, to treat the geometry as a surface signal and employ signal processing and compression techniques, such as wavelet compression [Khodakovsky et al. 2000].”
Recent advances in compression of 3D meshes (2005, background): “The main idea behind semi-regular remeshing techniques [18, 9, 17, 24] is to consider a mesh representation to have three components: geometry, connectivity and parameterization, and assume that the last two components (i.”