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LOD modelling of polygonal models based on multiple choice optimisation

机译:基于多项选择优化的多边形模型的LOD建模

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We propose a new automatic method for generating LODs of a given polygonal model that is based on edge collapse simplification operation and exploits a variant of multiple choice optimization (MCO) framework by J. Wu and L. Kobbelt (2002). In an edge collapse algorithm, the way how to measure the geometric deviation caused by an edge collapse transformation plays a key role. We introduce a new measure of local geometric deviation and a memory efficient method for its global evaluation; these local and global evaluation techniques are simple to implement, involve short execution times, and preserve geometric features and discontinuities automatically. Results and numerical comparisons show that our algorithm generates simplified models at different LODs of good visual fidelity, and consumes less memory and performs better in automatically preserving visually important features than other methods especially QSlim by M. Garland and P. S. Heckbert (1997).
机译:我们提出了一种新的自动生成给定多边形模型的LOD的方法,该方法基于边折叠简化操作,并利用了J. Wu和L. Kobbelt(2002)的多选优化(MCO)框架的变体。在边缘塌陷算法中,如何测量由边缘塌陷变换引起的几何偏差的方法起着关键作用。我们介绍了一种局部几何偏差的新度量,以及一种对其全局评估有效的记忆方法;这些局部和全局评估技术易于实施,执行时间短,并自动保留几何特征和不连续性。结果和数值比较表明,与M.Garland和P.S.Heckbert(1997)提出的QSlim方法相比,我们的算法在具有良好视觉保真度的不同LOD上生成了简化的模型,并且消耗较少的内存并在自动保留视觉上重要的功能方面表现更好。

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