Segmental Offset-Mapping Parallel Coordinates for Multidimensional Integer Dataset

Hui Li, Qin He, Hong Bao, Nan Ma, Guilin Pang
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引用次数: 1

Abstract

To visualize and analysis the multidimensional integer dataset, we present a visualization method named segmental offset-mapping parallel coordinates. The method first counted and calculated the proportion of each integer value in each dimension. The stacked coordinate axis was adopted to express the distribution of data in each dimension. The offset-mapping technology was introduced to obtain corresponding points in axes. The position of corresponding points could be different even the same integer value in different record using offset-mapping. The corresponding points was scattered over segment in the stacked coordinate axis using the offset-mapping technology. The offset-mapping technology can improve the capability of expressing the correlativity between the adjacent dimensions effectively for the multidimensional integer dataset. Road scene data in the unmanned driving field was selected as the experimental dataset in this paper. The experimental results prove the method presented in the paper can achieve obvious expression to the correlativity between the adjacent dimension data. The method can effectively improve the matching and analysis efficiency of road scene data in the unmanned driving field.
多维整数数据集的分段偏移映射并行坐标
为了对多维整数数据集进行可视化分析,提出了一种分段偏移映射并行坐标的可视化方法。该方法首先对每个维度中每个整数值的占比进行计数和计算。采用堆叠坐标轴表示各维数据的分布。引入偏移映射技术,得到坐标轴上相应的点。使用偏移映射,即使不同记录中的整数值相同,对应点的位置也可能不同。利用偏移映射技术将相应的点分散在堆叠坐标轴上的段上。偏移映射技术可以有效地提高多维整数数据集的邻维相关性表达能力。本文选取无人驾驶领域的道路场景数据作为实验数据集。实验结果表明,本文提出的方法能较好地表达相邻维数据之间的相关性。该方法可有效提高无人驾驶领域道路场景数据的匹配和分析效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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