Compression of Complex Animated Meshes

Amjoun, Rachida; Sondershaus, Ralf; Straßer, Wolfgang

doi:10.1007/11784203_57

Cited by 12 publications

(12 citation statements)

References 7 publications

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“…We compare our algorithm with several state-of-the-art methods, i.e., the partitioned ASM (PASM) [4], the Relative Local PCA (RLPCA) [30], and the RLPCA with motion similarity (we refer to it as MRLPCA here) [31].…”

Section: Methodsmentioning

confidence: 99%

“…However, their definition for motion information separates the motion magnitude from the motion direction, and thus results in a suboptimal measure for the actual motion. Amjoun et al [30] partitioned the meshes of the animation sequence into patches based on Euclidean distance, aligned the set of corresponding surface patches from the sequence with respect to the seed face, and then used a local PCA for coding each surface patch. The work in [31] followed the method in [30] with additional consideration of motion similarity for the segmentation.…”

Section: Related Workmentioning

confidence: 99%

“…Amjoun et al [30] partitioned the meshes of the animation sequence into patches based on Euclidean distance, aligned the set of corresponding surface patches from the sequence with respect to the seed face, and then used a local PCA for coding each surface patch. The work in [31] followed the method in [30] with additional consideration of motion similarity for the segmentation. They defined the local similarity based on the absolute vertex deviation between adjacent frames from the animation sequence.…”

Section: Related Workmentioning

confidence: 99%

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Using surface variability characteristics for segmentation of deformable 3D objects with application to piecewise statistical deformable model

Hua

Feng

2011

Vis Comput

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To cope with the small sample size problem in the construction of Statistical Deformable Models (SDM), this paper proposes two novel measures that quantify the similarity of the variability characteristics among deforming 3D meshes. These measures are used as the basis of our proposed technique for partitioning a 3D mesh for the construction of piecewise SDM in a divide-and-conquer strategy. Specifically, the surface variability information is extracted by performing a global principal component analysis on the set of sample meshes. An iterative face clustering algorithm is developed for segmenting a mesh that favors grouping triangular faces having similar variability characteristics into a same mesh component. We apply the proposed mesh segmentation algorithm to the construction of piecewise SDM and evaluate the representational ability of the resulting piecewise SDM through the reconstruction of unseen meshes. Experimental results show that our approach P. Du ( ) · H.outperforms several state-of-the-art methods in terms of the representational ability of the resulting piecewise SDM as evaluated by the reconstruction accuracy.

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Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Using surface variability characteristics for segmentation of deformable 3D objects with application to piecewise statistical deformable model

Hua

Feng

2011

Vis Comput

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“…Based on the geometry image coding introduced in [40], geometry video coding is proposed [25]. Progressive approaches can also be applied to animated data, examples based on wavelet decomposition being provided in [29,46] and based on clustering in [3].…”

Section: Animated Mesh Compressionmentioning

confidence: 99%

“…In the first one, the mesh is segmented and its motion encoded individually. The segmentation can be performed on surfaces [3,60] or in volumes [48,61]. A typical group are deformation controllers [59], mostly using an underlying skeleton.…”

Section: Animated Mesh Compressionmentioning

confidence: 99%

MPEG-4 Part 25: A graphics compression framework for XML-based scene graph formats

Jovanova¹,

Preda²,

Prêteux³

2009

Signal Processing: Image Communication

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Predictive compression of animated 3D models by optimized weighted blending of key‐frames

Hajizadeh

Ebrahimnezhad

2015

Computer Animation & Virtual

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Efficient compression techniques are required for animated mesh sequences with fixed connectivity and time‐varying geometry. In this paper, we propose a key‐frame‐based technique for three‐dimensional dynamic mesh compression. First, key‐frames are extracted from the animated sequence. Extracted key‐frames are then linearly combined using blending weights to predict the vertex locations of the other frames. These blending weights play a key role in the proposed algorithm because the prediction performance and the required number of key‐frames greatly depend on these weights. We present a novel method in order to compute the optimum blending weight that makes it possible to predict location of the vertices of the non‐key frames with the minimum number of key‐frames. The residual prediction errors are finally quantized and encoded using Huffman coding and another heuristic method. Experimental results on different test sequences with various sizes, topologies, and geometries demonstrate the privileged performance of the proposed method compared with the previous techniques. Copyright © 2015 John Wiley & Sons, Ltd.

show abstract

Compression of Complex Animated Meshes

Cited by 12 publications

References 7 publications

Using surface variability characteristics for segmentation of deformable 3D objects with application to piecewise statistical deformable model

Using surface variability characteristics for segmentation of deformable 3D objects with application to piecewise statistical deformable model

MPEG-4 Part 25: A graphics compression framework for XML-based scene graph formats

Predictive compression of animated 3D models by optimized weighted blending of key‐frames

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