Single-rate near lossless compression of animated geometry

Amjoun, Rachida; Straíer, Wolfgang

doi:10.1016/j.cad.2009.02.013

Cited by 11 publications

(7 citation statements)

References 10 publications

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“…Zhang and Owen [2007] and Müller et al [2006] place vertex displacement vectors into a hierarchical tree structure (an octree), which allows exploitation of spatiotemporal coherence. Amjoun and Straßer [2009] proposed using local coordinate systems (that separate tangential and normal components) to encode delta vectors. Stefanoski and Liu [2007] proposed simplifying the frames into spatial layers (i.e., levels of detail) and then exploiting spatial and temporal dependencies between neighboring spatial layers and consecutive frames to estimate the motion of each vertex.…”

Section: Methods Using Spatiotemporal Predictionmentioning

confidence: 99%

“…Before starting, we have to provide some insight into the useful functionalities of a dynamic mesh compression algorithm. We distinguish two main features that characterize existing algorithms: -Local versus global: As raised in Amjoun and Straßer [2009], some algorithms analyze the global coherence of the dynamic mesh to compress it, whereas on the other side, others focus on local frame-to-frame changes. The main benefit of global approaches is an improved compression performance, whereas local algorithms allow for faster (often real-time) compression/decompression.…”

Section: State Of the Art On Mesh Sequence Compressionmentioning

confidence: 99%

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3D Mesh Compression

Maglo¹,

et al. 2015

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3D meshes are commonly used to represent virtual surface and volumes. However, their raw data representations take a large amount of space. Hence, 3D mesh compression has been an active research topic since the mid 1990s. In 2005, two very good review articles describing the pioneering works were published. Yet, new technologies have emerged since then. In this article, we summarize the early works and put the focus on these novel approaches. We classify and describe the algorithms, evaluate their performance, and provide synthetic comparisons. We also outline the emerging trends for future research.

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Section: Methods Using Spatiotemporal Predictionmentioning

confidence: 99%

Section: State Of the Art On Mesh Sequence Compressionmentioning

confidence: 99%

3D Mesh Compression

Maglo¹,

et al. 2015

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“…Moreover, Khodakovsky et al [14] proposed to apply predictive method and arithmetic encoding on wavelet transform coefficients. Amjoun and Straβer [15] introduced a new connectivityguided predictive scheme to encode the residues in the local coordinate frames to improve the efficiency of animation compression. Stefanoski and Ostermann [16] presented a fast and efficient scalable predictive coding (SPC) scheme by employing predictive encoding in the space of rotation-invariant coordinates with respect to a spatially and temporally scalable decomposition of dynamic animation.…”

Section: Related Workmentioning

confidence: 99%

Spectral Animation Compression

Wang

Liu

Guo

et al. 2015

J. Comput. Sci. Technol.

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This paper presents a spectral approach to compress dynamic animation consisting of a sequence of homeomorphic manifold meshes. Our new approach directly compresses the field of deformation gradient defined on the surface mesh, by decomposing it into rigid-body motion (rotation) and non-rigid-body deformation (stretching) through polar decomposition. It is known that the rotation group has the algebraic topology of 3D ring, which is different from other operations like stretching. Thus we compress these two groups separately, by using Manifold Harmonics Transform to drop out their high-frequency details. Our experimental result shows that the proposed method achieves a good balance between the reconstruction quality and the compression ratio. We compare our results quantitatively with other existing approaches on animation compression, using standard measurement criteria.

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“…In addition, a number of previous research efforts [5,6,20,42] have been focused on connectivitybased compression. Their core idea is to exploit connectivity information of a mesh.…”

Section: Related Workmentioning

confidence: 99%