A Statistics-based Dimension Reduction of the Space of Path Line Attributes for Interactive Visual Flow Analysis
Abstract
Recent work has shown the great potential of interactive flow analysis by the analysis of path lines. The choice of suitable attributes, describing the path lines, is, however, still an open question. This paper addresses this question performing a statistical analysis of the path line attribute space. In this way we are able to balance the usage of computing power and storage with the necessity to not loose relevant information. We demonstrate how a carefully chosen attribute set can improve the benefits of state-of-the art interactive flow analysis. The results obtained are compared to previously published work.
A. Pobitzer, A. Lez, K. Matkovic, and H. Hauser, "A Statistics-based Dimension Reduction of the Space of Path Line Attributes for Interactive Visual Flow Analysis," in Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2012), 2012, p. 113–120.
[BibTeX]
Recent work has shown the great potential of interactive flow analysis by the analysis of path lines. The choice of suitable attributes, describing the path lines, is, however, still an open question. This paper addresses this question performing a statistical analysis of the path line attribute space. In this way we are able to balance the usage of computing power and storage with the necessity to not loose relevant information. We demonstrate how a carefully chosen attribute set can improve the benefits of state-of-the art interactive flow analysis. The results obtained are compared to previously published work.
@INPROCEEDINGS {Pobitzer12AStatistics,
author = "Armin Pobitzer and Alan Lez and Kresimir Matkovic and Helwig Hauser",
title = "A Statistics-based Dimension Reduction of the Space of Path Line Attributes for Interactive Visual Flow Analysis",
booktitle = "Proceedings of the IEEE Pacific Visualization Symposium (PacificVis 2012)",
year = "2012",
pages = "113--120",
month = "March",
abstract = "Recent work has shown the great potential of interactive flow analysis by the analysis of path lines. The choice of suitable attributes, describing the path lines, is, however, still an open question. This paper addresses this question performing a statistical analysis of the path line attribute space. In this way we are able to balance the usage of computing power and storage with the necessity to not loose relevant information. We demonstrate how a carefully chosen attribute set can improve the benefits of state-of-the art interactive flow analysis. The results obtained are compared to previously published work.",
pdf = "pdfs/Pobitzer12AStatistics.pdf",
images = "images/Pobitzer12AStatistics.png",
thumbnails = "images/Pobitzer12AStatistics_thumb.png",
location = "Songdo, Korea"
}