KAUST DepartmentVisual Computing Center (VCC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computer Science Program
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AbstractWe present a novel method for high-quality blue-noise sampling on mesh surfaces with prescribed cell-sizes for the underlying tessellation (capacity constraint). Unlike the previous surface sampling approach that only uses capacity constraints as a regularizer of the Centroidal Voronoi Tessellation (CVT) energy, our approach enforces an exact capacity constraint using the restricted power tessellation on surfaces. Our approach is a generalization of the previous 2D blue noise sampling technique using an interleaving optimization framework. We further extend this framework to handle multi-capacity constraints. We compare our approach with several state-of-the-art methods and demonstrate that our results are superior to previous work in terms of preserving the capacity constraints.
CitationZhang S, Guo J, Zhang H, Jia X, Yan D-M, et al. (2016) Capacity constrained blue-noise sampling on surfaces. Computers & Graphics 55: 44–54. Available: http://dx.doi.org/10.1016/j.cag.2015.11.002.
SponsorsNational Natural Science Foundation of China[61572502, 61373070, 11201463, 61372168]
National Key Technologies R&D Program of China[2015BAF23B03]
Tsinghua University Initiative Scientific Research Program[2012Z02170]
JournalComputers & Graphics