Transgraph: Hierarchical exploration of transition relationships in time-varying volumetric data
Document Type
Article
Publication Date
11-15-2011
Abstract
A fundamental challenge for time-varying volume data analysis and visualization is the lack of capability to observe and track data change or evolution in an occlusion-free, controllable, and adaptive fashion. In this paper, we propose to organize a timevarying data set into a hierarchy of states. By deriving transition probabilities among states, we construct a global map that captures the essential transition relationships in the time-varying data. We introduce the TransGraph, a graph-based representation to visualize hierarchical state transition relationships. The TransGraph not only provides a visual mapping that abstracts data evolution over time in different levels of detail, but also serves as a navigation tool that guides data exploration and tracking. The user interacts with the TransGraph and makes connection to the volumetric data through brushing and linking. A set of intuitive queries is provided to enable knowledge extraction from time-varying data. We test our approach with time-varying data sets of different characteristics and the results show that the TransGraph can effectively augment our ability in understanding time-varying data. © 2011 IEEE.
Publication Title
IEEE Transactions on Visualization and Computer Graphics
Recommended Citation
Gu, Y.,
&
Wang, C.
(2011).
Transgraph: Hierarchical exploration of transition relationships in time-varying volumetric data.
IEEE Transactions on Visualization and Computer Graphics,
17(12), 2015-2024.
http://doi.org/10.1109/TVCG.2011.246
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/11147