文献类型：会议论文

英文题名：Segmental Offset-Mapping Parallel Coordinates for Multidimensional Integer Dataset

作者：Li, Hui[1]; He, Qin[1]; Bao, Hong[2]; Ma, Nan[2]; Pang, Guilin[2]

第一作者：李慧

通讯作者：He, Qin

机构：[1] College of Management, Beijing Union University, Beijing, 100101, China; [2] College of Robotics, Beijing Union University, Beijing, 100101, China

第一机构：北京联合大学管理学院

会议论文集：Proceedings - 13th International Conference on Computational Intelligence and Security, CIS 2017

会议日期：December 15, 2017 - December 18, 2017

会议地点：Hong Kong, Hong kong

语种：英文

外文关键词：Intelligent computing - Network security - Roads and streets

摘要：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. ? 2017 IEEE.