按曲率选取基点的多分辨率表示重构算法
A New Multiresolution Representation Approach Based on Curvature
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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.Abstract: 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.
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