Umfassende visuelle Informationssuche in multidimensionalen Datensätzen

多维数据集中的综合视觉信息搜索

• 批准号: 81548357
• 负责人: Professor Dr.-Ing. Marcus Magnor
• 金额: --
• 依托单位: Institut für Simulation und Graphik
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2008
• 资助国家: 德国
• 起止时间: 2007-12-31 至 2014-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/81548357?language=en
• 关键词: Umfassende; visuelle; Informationssuche; multidimensionalen; Datens

The project extends the results of the exhaustive visual search approach to address higher-order relations in multidimensional data sets which are to be searched, modeled, and analyzed by applying image analysis techniques to a large number of automatically created visualizations. Here, “higher-order relations“ refers to considering non-trivial relations between two dimensions described by user-drawn sketches, relations between more than two dimensions, and relations only present in continuous (nondiscrete) data sets. For all three cases, solutions based on the exhaustive visual search shall be explored. Methodically, the approaches are based on finding new quality measures for different visualizations, analyzing 3D visualizations, and searching features in continuous visualizations. While focusing on developing general (application-independent) principles, our methods will be tested on high-dimensional and large data sets provided by our cooperation partners from climate research and medical imaging.

该项目扩展了详尽的视觉搜索方法的结果，以解决多维数据集中的高阶关系，这些数据集将通过将图像分析技术应用于大量自动创建的可视化来进行搜索、建模和分析。考虑用户绘制的草图描述的两个维度之间的非平凡关系、两个以上维度之间的关系以及仅存在于连续（非离散）数据集中的关系对于所有三种情况，应采用基于详尽视觉搜索的解决方案。系统性地，这些方法基于寻找不同可视化的新质量度量、分析 3D 可视化以及搜索连续可视化中的特征，同时专注于开发通用（独立于应用程序）原则，我们的方法将在高维和高维度上进行测试。我们的气候研究和医学成像合作伙伴提供的大数据集。