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Interactive Visualization of Function Fields by Range‐Space Segmentation
Author(s) -
Anderson John C.,
Gosink Luke J.,
Duchaineau Mark A.,
Joy Kenneth I.
Publication year - 2009
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.1467-8659.2009.01480.x
Subject(s) - visualization , computer science , segmentation , range (aeronautics) , dimensionality reduction , data visualization , scalar (mathematics) , function (biology) , dimension (graph theory) , field (mathematics) , artificial intelligence , pattern recognition (psychology) , data mining , mathematics , geometry , materials science , composite material , evolutionary biology , pure mathematics , biology
We present a dimension reduction and feature extraction method for the visualization and analysis of function field data. Function fields are a class of high‐dimensional, multi‐variate data in which data samples are one‐dimensional scalar functions. Our approach focuses upon the creation of high‐dimensional range‐space segmentations, from which we can generate meaningful visualizations and extract separating surfaces between features. We demonstrate our approach on high‐dimensional spectral imagery, and particulate pollution data from air quality simulations.