CASIA OpenIR  > 模式识别国家重点实验室  > 多媒体计算与图形学
叶畋宇; 王逸群; 严冬明; 雍俊海
Source Publication系统仿真学报
Abstract重心 Voronoi 图(Centroidal Voronoi tessellation,CVT) 是一个重要的几何结构,在地理信息系统,信号处理,网格生成/优化,可视化等领域有着重要应用。针对传统全局生成、优化的方法的不足,比如奇异点多、收敛速度较慢等问题,本文提出了“生成优化”与“随机扰动”等两种局部优化方法,以及一个整合了层次生成、局部优化、蒙特卡罗优化的CVT生成算法框架。实验结果表明,相比于已有算法,本文的方法在速度与质量上有综合的提升。
Other AbstractCentroidal Voronoi tessellation is a special geometric structure, which has many applications in various field, such as geographical information system, signal processing, mesh generation/optimization, visualization and so on. Due to the highly non-convex nature of the CVT energy function, the existing methods for computing CVT have several drawbacks, which always trap into local minima. In this paper, we propose "generation optimization" and "stochastic optimization" schemes to further reduce the CVT energy. Experimental results show that the proposed method improves both quality and efficiency compared to recent approaches.
Document Type期刊论文
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GB/T 7714
叶畋宇,王逸群,严冬明,等. 基于局部优化的重心Voronoi图计算[J]. 系统仿真学报,2017,xx(xx):xx.
APA 叶畋宇,王逸群,严冬明,&雍俊海.(2017).基于局部优化的重心Voronoi图计算.系统仿真学报,xx(xx),xx.
MLA 叶畋宇,et al."基于局部优化的重心Voronoi图计算".系统仿真学报 xx.xx(2017):xx.
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