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搜索，建模和分析。在这里，“高阶关系”是指考虑用户绘制草图所描述的两个维度之间的非平凡关系，超过两个维度之间的关系以及仅在连续（Nondscrete）数据集中存在的关系。对于所有三种情况，均应探索基于详尽视觉搜索的解决方案。有条理地，这些方法基于寻找不同可视化的新质量度量，分析3D可视化和连续可视化中的搜索功能。在专注于制定一般（无关）原则的同时，我们的方法将在我们的合作伙伴通过气候研究和医学成像提供的合作伙伴提供的高维和大数据集进行测试。