基于点云的精细平面距离估计

Natalija Chmelařová, P. Chmelar, L. Rejfek
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引用次数: 1

摘要

本文主要研究精细平面估计问题。对于平面检测,使用水平连通分量标记算法。精确的平面位置由平面在扫描维度上的点直方图决定。到目前为止,最终飞机的范围都是通过一个参数手动选择的。输入点云中的平面存在表示扫描维度中较高的点的浓度,高于平均值。两侧的浓度从局部最大值开始下降。针对最优平面点距表达式,提出了弯头位置估计算法。实验部分给出了几个算例的实际结果,并给出了参数设置的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Fine Plane Range Estimation From Point Cloud
This paper deals with the fine plane estimation. For a plane detection the level connected component labeling algorithm is used. The precise plane position is determined by the plane’s points histogram in the scanning dimension. Up till now, the final plane’s range has been selected manually by a parameter. Plane presence in an input point cloud represents the higher points’ concentration in the scanning dimension, higher than average value. The concentration decreases on both sides from a local maximum value. This paper presents the algorithm of the elbows’ position estimation for the optimal plane’s points range expression. The experimental part shows practical results of several examples and gives recommendations for parameters setting.
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