The visual display of quantitative information
The visual display of quantitative information
Construction of line densities for parallel coordinate plots
Computing and graphics in statistics
Toolglass and magic lenses: the see-through interface
SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Metrics for effective information visualization
INFOVIS '97 Proceedings of the 1997 IEEE Symposium on Information Visualization (InfoVis '97)
Feature congestion: a measure of display clutter
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The sampling lens: making sense of saturated visualisations
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Improving 2D Scatterplots Effectiveness through Sampling, Displacement, and User Perception
IV '05 Proceedings of the Ninth International Conference on Information Visualisation
by chance enhancing interaction with large data sets through statistical sampling
Proceedings of the Working Conference on Advanced Visual Interfaces
Enabling Automatic Clutter Reduction in Parallel Coordinate Plots
IEEE Transactions on Visualization and Computer Graphics
A dynamic multiscale magnifying tool for exploring large sparse graphs
Information Visualization
General visualization abstraction algorithm for geographic map-based human-robot interfaces
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
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Previous work has demonstrated the use of random sampling in visualising large data sets and the practicality of a sampling lens in enabling focus+context viewing. Autosampling was proposed as a mechanism to maintain constant density within the lens without user intervention. However, this requires rapid calculation of density or clutter. This paper defines clutter in terms of the occlusion of plotted points and evaluates three possible occlusion metrics that can be used with parallel coordinate plots. An empirical study showed the relationship between these metrics was independent of location and could be explained with a surprisingly simple probabilistic model.