
handle: 1956/5858
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.
image processing: 429, data visualisation, interactive visual flow analysis, data analysis, path line attribute space, path line analysis, 004, VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation, Interactive Visual Flow Analysis, statistical analysis, Interactive Visual Flow Analysis, Time dependent flow, statistics-based dimension reduction, signal processing, Time dependent flow, visualization, :Mathematics and natural science: 400::Information and communication science: 420::Simulation, visualization, signal processing, image processing: 429 [VDP]
image processing: 429, data visualisation, interactive visual flow analysis, data analysis, path line attribute space, path line analysis, 004, VDP::Mathematics and natural science: 400::Information and communication science: 420::Simulation, Interactive Visual Flow Analysis, statistical analysis, Interactive Visual Flow Analysis, Time dependent flow, statistics-based dimension reduction, signal processing, Time dependent flow, visualization, :Mathematics and natural science: 400::Information and communication science: 420::Simulation, visualization, signal processing, image processing: 429 [VDP]
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
