Evaluation of Glyph-based Multivariate Scalar Volume Visualization Techniques.

David Feng, Yueh Lee, Lester Kwock, Russell M Taylor
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引用次数: 18

Abstract

We present a user study quantifying the effectiveness of Scaled Data-Driven Spheres (SDDS), a multivariate three-dimensional data set visualization technique. The user study compares SDDS, which uses separate sets of colored sphere glyphs to depict variable values, to superquadric glyphs, an alternative technique that maps all variable values to a single glyph. User study participants performed tasks designed to measure their ability to estimate values of particular variables and identify relationships among variables. Results from the study show that users were significantly more accurate and faster for both tasks under the SDDS condition.

基于符号的多变量标量体可视化技术评价。
我们提出了一项用户研究,量化了尺度数据驱动球体(SDDS)的有效性,这是一种多变量三维数据集可视化技术。用户研究将SDDS(使用单独的彩色球体字形集来描绘变量值)与超二次字形(一种将所有变量值映射到单个字形的替代技术)进行了比较。用户研究参与者执行的任务旨在衡量他们估计特定变量值和识别变量之间关系的能力。研究结果表明,在SDDS条件下,用户对两项任务的准确率和速度都显著提高。
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