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Eigenspace compression: dynamic 3D mesh compression by restoring fine geometry to deformed coarse models

机译:特征空间压缩:通过将​​精细的几何体还原为变形的粗略模型来进行动态3D网格压缩

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摘要

Dynamic 3D mesh compression is of great practical important issues in computer graphics and multimedia applications. In this paper, an efficient compression algorithm is proposed to represent animated mesh sequences in a compact way, so that the storage and transmission of dynamic 3D meshes can be accomplished efficiently. The focus of this paper is on the animated mesh sequences with shared connectivity. The proposed method first computes coarse models (low frequency modes) of the animated sequence using the graph Laplacian matrix. Obtained coordinate weights are used at the decoder to reconstruct the coarse models of the sequence. Then, a novel approach is proposed to extract fixed details (high frequency modes or finer features) of the animated mesh. Finally, a details restoration process is applied at the decoder to add details back to the coarse models of the reconstructed sequence. The superiority of the proposed method to the current state of the arts is demonstrated in terms of low data rates for a given degree of perceived distortion.
机译:在计算机图形和多媒体应用中,动态3D网格压缩是非常重要的实际重要问题。本文提出了一种有效的压缩算法来紧凑地表示动画网格序列,从而可以有效地完成动态3D网格的存储和传输。本文的重点是具有共享连通性的动画网格序列。所提出的方法首先使用图拉普拉斯矩阵来计算动画序列的粗略模型(低频模式)。在解码器处使用获得的坐标权重来重建序列的粗略模型。然后,提出了一种新颖的方法来提取动画网格的固定细节(高频模式或更精细的特征)。最后,在解码器处应用细节恢复过程,以将细节添加回重构序列的粗略模型。对于给定程度的感知失真,低数据速率证明了所提出方法相对于现有技术的优越性。

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