Progressive compression is one of the most effective multi-resolution schemes for sending large 3D meshes in a network environment. However, if we change the 3D meshes, i.e., adding watermarks or changing the pose of models, the deformed 3D mesh model should be compressed again from scratch and it may take too much time especially for large mesh models. In this paper, we greatly reduce the compression time for deformed models, which we call recompression, when connectivity-preserving deformation is applied to mesh models. We first compress a large mesh progressively using a wavelet-based method, and then extract vertices and wavelet coefficients affected by deformed area using our propagation algorithm. Direct modification acts on the required elements using original matrix filters without additional postprocessing, boosting compression performance. Our method increases the recompression speed up to 17 fold compared with the original speed, even if the entire mesh is deformed. We also show that the speedup increases up to 33 fold when local deformation acts on the local regions comprising 5% of mesh.

渐进压缩是在网络环境中发送大型3D网格的最有效的多分辨率方案之一。但是，如果我们更改3D网格，即添加水印或更改模型的姿势，则应重新从头开始压缩变形的3D网格模型，这可能会花费太多时间，特别是对于大型网格模型。在本文中，我们大大减少了变形模型的压缩时间，我们称之为再压缩，当将保持连通性的变形应用于网格模型时。我们首先使用基于小波的方法逐步压缩大网格，然后使用传播算法提取受变形区域影响的顶点和小波系数。直接修改使用原始矩阵滤波器对所需元素进行操作，而无需进行额外的后处理，从而提高了压缩性能。即使整个网格变形，我们的方法也可以将重新压缩速度提高到原始速度的17倍。我们还表明，当局部变形作用于包含5％网格的局部区域时，加速比最多增加33倍。