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Scalable Linear Predictive Coding of Time-Consistent 3D Mesh Sequences

机译:时间一致3D网格序列的可扩展线性预测编码

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We present a linear predictive compression approach for time-consistent 3D mesh sequences supporting and exploiting scalability. The algorithm decomposes each frame of a mesh sequence in layers employing patch-based mesh simplification techniques. This layered decomposition is consistent in time. Following the predictive coding paradigm, local temporal and spatial dependencies between layers and frames are exploited for compression. Prediction is performed vertex-wise from coarse to fine layers exploiting the motion of already encoded 1-ring neighbor vertices for prediction of the current vertex location. It is shown that a predictive exploitation of the proposed layered configuration of vertices can improve the compression performance upon other state-of-the-art approaches by up to 16% in domains relevant for applications.
机译:我们为支持和利用可扩展性的时间一致的3D网格序列提出了线性预测压缩方法。该算法在采用基于补丁的网格简化技术的层中分解网格序列的每个帧。该分层分解及时一致。在预测编码范式之后,利用层和帧之间的本地时间和空间依赖性进行压缩。从粗略地执行从粗略到微层的顶点执行预测,利用已经编码的1-环邻顶点的运动以预测当前顶点位置。结果表明,预测的顶点的分层配置的预测开发可以在与应用程序相关的域中的其他最先进的方法上提高压缩性能,该方法高达16%。

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