实时点云细化

Gaël Guennebaud, L. Barthe, M. Paulin
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引用次数: 13

摘要

基于喷溅的渲染技术是目前对基于点的几何图形进行高效、高质量渲染的最佳选择。然而,这种技术不适合大的放大倍率,特别是当对象是采样不足。本文采用一种基于点的几何图形的快速动态上采样算法,提高了纯喷溅技术的渲染质量。我们的算法的灵感来自插值细分曲面,其中几何是迭代细化。在每一步中,精炼的几何形状都是由前一步的一组新的点来丰富的。点插入过程使用三个算子:一个局部邻域选择算子,一个细化算子(添加新的点)和一个平滑算子。尽管我们的插入过程使极限曲面的分析变得复杂,并且不能保证其G1连续性,但对于高质量的实时点渲染来说,它仍然是非常有效的。事实上,虽然提供了更高的渲染质量,特别是对于大倍率,我们的算法不需要其他预处理,也不需要任何飞溅技术所使用的任何额外信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-Time Point Cloud Refinement
Splatting-based rendering techniques are currently the best choice for efficient high quality rendering of pointbased geometries. However, such techniques are not suitable for large magnification, especially when the object is under-sampled. This paper improves the rendering quality of pure splatting techniques using a fast dynamic up-sampling algorithm for point-based geometry. Our algorithm is inspired by interpolatory subdivision surfaces where the geometry is refined iteratively. At each step the refined geometry is that from the previous step enriched by a new set of points. The point insertion procedure uses three operators: a local neighborhood selection operator, a refinement operator (adding new points) and a smoothing operator. Even though our insertion procedure makes the analysis of the limit surface complicated and it does not guarantee its G1 continuity, it remains very efficient for high quality real-time point rendering. Indeed, while providing an increased rendering quality, especially for large magnification, our algorithm needs no other preprocessing nor any additional information beyond that used by any splatting technique.
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