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A Screen Space Quality Method for Data Abstraction
Author(s) -
Johansson J.,
Cooper M.
Publication year - 2008
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2008.01240.x
Subject(s) - computer science , abstraction , rendering (computer graphics) , interactive visual analysis , representation (politics) , data mining , data space , data set , set (abstract data type) , measure (data warehouse) , computer graphics (images) , space (punctuation) , artificial intelligence , visualization , data visualization , programming language , philosophy , epistemology , politics , political science , law , operating system
The rendering of large data sets can result in cluttered displays and non‐interactive update rates, leading to time consuming analyses. A straightforward solution is to reduce the number of items, thereby producing an abstraction of the data set. For the visual analysis to remain accurate, the graphical representation of the abstraction must preserve the significant features present in the original data. This paper presents a screen space quality method, based on distance transforms, that measures the visual quality of a data abstraction. This screen space measure is shown to better capture significant visual structures in data, compared with data space measures. The presented method is implemented on the GPU, allowing interactive creation of high quality graphical representations of multivariate data sets containing tens of thousands of items.