Display of Surfaces from Volume Data
IEEE Computer Graphics and Applications
Generation of transfer functions with stochastic search techniques
Proceedings of the 7th conference on Visualization '96
VIS '97 Proceedings of the 8th conference on Visualization '97
Semi-automatic generation of transfer functions for direct volume rendering
VVS '98 Proceedings of the 1998 IEEE symposium on Volume visualization
Proceedings of the conference on Visualization '01
Tracking and Visualizing Turbulent 3D Features
IEEE Transactions on Visualization and Computer Graphics
Visualizing Time-Varying Volume Data
Computing in Science and Engineering
Cluster and Calendar Based Visualization of Time Series Data
INFOVIS '99 Proceedings of the 1999 IEEE Symposium on Information Visualization
Volume Tracking Using Higher Dimensional Isosurfacing
Proceedings of the 14th IEEE Visualization 2003 (VIS'03)
Intelligent Feature Extraction and Tracking for Visualizing Large-Scale 4D Flow Simulations
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Visualization and exploration of time-varying medical image data sets
GI '07 Proceedings of Graphics Interface 2007
Multiscale Time Activity Data Exploration via Temporal Clustering Visualization Spreadsheet
IEEE Transactions on Visualization and Computer Graphics
Importance-Driven Time-Varying Data Visualization
IEEE Transactions on Visualization and Computer Graphics
Visualizing time-varying features with TAC-based distance fields
PACIFICVIS '09 Proceedings of the 2009 IEEE Pacific Visualization Symposium
Time histograms for large, time-dependent data
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
Case study: visual analysis of complex, time-dependent simulation results of a diesel exhaust system
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
Simultaneous classification of time-varying volume data based on the time histogram
EUROVIS'06 Proceedings of the Eighth Joint Eurographics / IEEE VGTC conference on Visualization
An exploratory technique for coherent visualization of time-varying volume data
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
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When creating transfer functions for time-varying data, it is not clear what range of values to use for classification, as data value ranges and distributions change over time. In order to generate time-varying transfer functions, we search the data for classes that have similar behavior over time, assuming that data points that behave similarly belong to the same feature. We utilize a method we call temporal clustering and sequencing to find dynamic features in value space and create a corresponding transfer function. First, clustering finds groups of data points that have the same value space activity over time. Then, sequencing derives a progression of clusters over time, creating chains that follow value distribution changes. Finally, the cluster sequences are used to create transfer functions, as sequences describe the value range distributions over time in a data set.