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朱素佳, 孙国道, 江棨, 夏旺, 梁荣华. 高密度群体轨迹数据的微观可视分析[J]. 计算机辅助设计与图形学学报, 2020, 32(12): 1871-1880. DOI: 10.3724/SP.J.1089.2020.18206
引用本文: 朱素佳, 孙国道, 江棨, 夏旺, 梁荣华. 高密度群体轨迹数据的微观可视分析[J]. 计算机辅助设计与图形学学报, 2020, 32(12): 1871-1880. DOI: 10.3724/SP.J.1089.2020.18206
Zhu Sujia, Sun Guodao, Jiang Qi, Xia Wang, Liang Ronghua. Microscopic Visual Analysis of High-Density Group Trajectory Data[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(12): 1871-1880. DOI: 10.3724/SP.J.1089.2020.18206
Citation: Zhu Sujia, Sun Guodao, Jiang Qi, Xia Wang, Liang Ronghua. Microscopic Visual Analysis of High-Density Group Trajectory Data[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(12): 1871-1880. DOI: 10.3724/SP.J.1089.2020.18206

高密度群体轨迹数据的微观可视分析

Microscopic Visual Analysis of High-Density Group Trajectory Data

  • 摘要: 人类活动会持续产生大量时空轨迹数据,探索和理解数据中的隐藏模式可帮助理解人类生产生活的规律、提高管理效率.前人工作大多关注于轨迹数据的宏观可视分析,缺乏对高密度小区域内的个体行为展开深入分析.针对高密度群体轨迹数据,提出多视图结合的可视分析方法以探索和分析其微观演化情况.该方法主要包括4个部分:基于small-multiples的特征统计视图,展示轨迹数据在时间和空间维度上的特征分布;采用多分辨率河流视图支持从多层次聚合角度展示轨迹数据的变化;采用轨迹投影视图揭示高密度群体轨迹间的相关性;采用多层次空间地图以展示轨迹数据的具体分布情况.上述方法形成的可视分析系统已用于2个高密度群体轨迹数据集的分析中,为后续高密度群体轨迹数据的可视分析提供一种解决思路.

     

    Abstract: People’s daily life is surrounded by Spatio-temporal trajectory datasets.Exploring and understanding the hidden patterns can help us grasp the characteristics of human productivity and improve management efficiency.Most previous works focused on the macroscopic analysis of trajectory datasets and lacked in-depth analysis of individual behaviors within high-density trajectory datasets in a small region.In this paper,we proposed a visual analysis system to analyze the high-density trajectory datasets.The method consists of four components,a small-multiples based feature statistical view for showing the features of various dimensions within dataset,a glyph-embedded multi-stream view for displaying overall evolution patterns and highlight critical modes,a projection view for illustrating the relative correlation among trajectories,and a multi-mode hierarchical spatial map for presenting detailed characteristics in the dataset.The interactive system has been used in two trajectory datasets to provide a solution for visually analyzing high-density trajectory datasets.

     

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