Dynamic mesh sequence (DMS) is a simple and accurate representation for precisely recording a 3D animation sequence. Despite its simplicity, this representation is typically large in data size, making storage and transmission expensive. This paper presents a novel framework that allows effective DMS compression and progressive streaming by eliminating spatial and temporal redundancy. To explore temporal redundancy, we propose a temporal frame‐clustering algorithm to organize DMS frames by their motion trajectory changes, eliminating intracluster redundancy by principal component analysis dimensionality reduction. To eliminate spatial redundancy, we propose an algorithm to transform the coordinates of mesh vertex trajectory into a decorrelated trajectory space, generating a new spatially nonredundant trajectory representation. We finally apply a spectral graph wavelet transform with color set partitioning embedded block encoding to turn the resultant DMS into a multiresolution representation to support progressive streaming. Experiment results show that our method outperforms several existing methods in terms of storage requirement and reconstruction quality.

中文翻译：

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用于渐进式流媒体的压缩动态网格序列

动态网格序列 (DMS) 是一种简单而准确的表示，用于精确记录 3D 动画序列。尽管它很简单，但这种表示通常数据量很大，使得存储和传输成本高昂。本文提出了一种新颖的框架，它通过消除空间和时间冗余来实现有效的 DMS 压缩和渐进式流传输。为了探索时间冗余，我们提出了一种时间帧聚类算法，通过它们的运动轨迹变化来组织 DMS 帧，通过主成分分析降维来消除簇内冗余。为了消除空间冗余，我们提出了一种算法，将网格顶点轨迹的坐标转换为去相关的轨迹空间，生成新的空间非冗余轨迹表示。我们最终应用带有颜色集分区嵌入块编码的频谱图小波变换，将生成的 DMS 转换为多分辨率表示以支持渐进式流媒体。实验结果表明，我们的方法在存储需求和重建质量方面优于现有的几种方法。