用于运动视觉分析的时空聚合

G. Andrienko, N. Andrienko
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引用次数: 246

摘要

通过目前的跟踪技术,各种物体的运动数据被收集得越来越多。传统的运动数据可视化和交互式探索方法无法处理如此大的数据。在本文中,我们探讨了使用聚合对运动数据进行可视化分析的方法。我们定义了适合运动数据的聚合方法,并找到了可视化和交互技术来表示聚合结果,从而实现对数据的全面探索。我们考虑了两种可能的运动观点,交通导向和轨迹导向。每个视图需要不同的分析和数据聚合方法。我们用米兰跟踪多辆汽车的示例数据和城市交通管理领域的示例分析任务来说明我们的论点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatio-temporal aggregation for visual analysis of movements
Data about movements of various objects are collected in growing amounts by means of current tracking technologies. Traditional approaches to visualization and interactive exploration of movement data cannot cope with data of such sizes. In this research paper we investigate the ways of using aggregation for visual analysis of movement data. We define aggregation methods suitable for movement data and find visualization and interaction techniques to represent results of aggregations and enable comprehensive exploration of the data. We consider two possible views of movement, traffic-oriented and trajectory-oriented. Each view requires different methods of analysis and of data aggregation. We illustrate our argument with example data resulting from tracking multiple cars in Milan and example analysis tasks from the domain of city traffic management.
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