A Framework for Multiclass Contour Visualization.
IEEE Trans Vis Comput Graph
; 29(1): 353-362, 2023 Jan.
Article
em En
| MEDLINE
| ID: mdl-36194705
ABSTRACT
Multiclass contour visualization is often used to interpret complex data attributes in such fields as weather forecasting, computational fluid dynamics, and artificial intelligence. However, effective and accurate representations of underlying data patterns and correlations can be challenging in multiclass contour visualization, primarily due to the inevitable visual cluttering and occlusions when the number of classes is significant. To address this issue, visualization design must carefully choose design parameters to make visualization more comprehensible. With this goal in mind, we proposed a framework for multiclass contour visualization. The framework has two components a set of four visualization design parameters, which are developed based on an extensive review of literature on contour visualization, and a declarative domain-specific language (DSL) for creating multiclass contour rendering, which enables a fast exploration of those design parameters. A task-oriented user study was conducted to assess how those design parameters affect users' interpretations of real-world data. The study results offered some suggestions on the value choices of design parameters in multiclass contour visualization.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
IEEE Trans Vis Comput Graph
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2023
Tipo de documento:
Article