中文摘要：

通过曲率引导选取一组基面来完成Eck等提出的任意拓扑三角网格多分辨率表示重构算法中的Voronoi划分．在提高效率的同时，可在相同网格规模下取得更好的重构质量；在重采样过程中以粗网格的Loop细分来指导参数域的细分，减轻了原算法因线性细分而产生的块状分界现象．最后提出一种自适应细分重采样技术，以减少数据冗余．

英文摘要：

We present a new approach to generate a multiresolution representation of meshes by selecting a set of sites based on curvature. Compared with the method proposed by Eck et al. , it improves not only the reconstruction efficiency but also the resampling quality. Furthermore, we propose a resampling strategy based on Loop subdivision to avoid obvious tiled boundaries and an adaptive refinement scheme to reduce data redundancy, respectively.