Low data loss point cloud to multi-line conversion and union

J. Králík, V. Venglár
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Abstract

Union of point clouds converted into lines is basically impossible nowadays. In big area mapping task, there is a problem how to represent scanned data. A point cloud is basic output from almost every mapping and environment scanning system, but as the area grows, there comes need for huge data storage and also the computation cost starts to grow rapidly. On the other side, curve representation is simple and easy to process, but all other data from point cloud get lost and further actualization of curve is basically impossible. In this article we present algorithms of robust procedure which can transfer point-cloud to curve and data. The final goal is to achieve the same result for two curves which are merged, as if two point-clouds were merged and transferred to curve.
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低数据丢失点云对多线路的转换和合并
将点云合并成线在目前基本上是不可能的。在大面积的测绘任务中,扫描数据如何表示是一个难题。点云几乎是每个测绘和环境扫描系统的基本输出,但随着面积的增长,需要大量的数据存储,计算成本也开始快速增长。另一方面,曲线表示简单,易于处理,但点云的其他数据都丢失了,曲线的进一步实现基本上是不可能的。本文提出了将点云转换为曲线和数据的鲁棒过程算法。最终的目标是对合并的两条曲线达到相同的结果,就好像两个点云合并并转移到曲线上一样。
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