Feature Extraction and Iconic Visualization
Feature Extraction and Iconic Visualization
复制标题
特征提取和标志性可视化
DOI：
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发表时间：
1996
影响因子：
5.2
通讯作者：
Frank J. Post
中科院分区：
文献类型：
--
作者：
T. Walsum;F. Post;D. Silver;Frank J. Post
我们提出了一个概念框架和特征提取和图标可视化的过程模型。特征是从数据集中提取的感兴趣区域。它们由属性集表示，属性集在可视化过程中起着关键作用。这些属性集被映射到图标或符号参数对象，以进行可视化。这些特性提供了对原始数据的紧凑抽象，而图标则是将它们可视化的自然方式。我们提出了提取特征和计算属性集的通用技术，并描述了一种简单但功能强大的建模语言，该语言是为了创建图标并将属性链接到图标参数而开发的。我们提出了说明性的例子与所描述的技术创建的图标可视化，显示这种方法的有效性。
We present a conceptual framework and a process model for feature extraction and iconic visualization. The features are regions of interest extracted from a dataset. They are represented by attribute sets, which play a key role in the visualization process. These attribute sets are mapped to icons, or symbolic parametric objects, for visualization. The features provide a compact abstraction of the original data, and the icons are a natural way to visualize them. We present generic techniques to extract features and to calculate attribute sets, and describe a simple but powerful modeling language which was developed to create icons and to link the attributes to the icon parameters. We present illustrative examples of iconic visualization created with the techniques described, showing the effectiveness of this approach.