Simplification of Node Position Data for Interactive Visualization of Dynamic Datasets

Abstract

We propose to aid the interactive visualization of time-varying spatial datasets by simplifying node position data over the entire simulation as opposed to over individual states. Our approach is based on two observations. The first observation is that the trajectory of some nodes can be approximated well without recording the position of the node for every state. The second observation is that there are groups of nodes whose motion from one state to the next can be approximated well with a single transformation. We present dataset simplification techniques that take advantage of this node data redundancy. Our techniques are general, supporting many types of simulations, they achieve good compression factors, and they allow rigorous control of the maximum node position approximation error. We demonstrate our approach in the context of finite element analysis data, of liquid flow simulation data, and of fusion simulation data.

Keywords: simplification of node positions, trajectory simplification, trajectory clustering, rigid body decomposition, interactive visualization, simulation data compression

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Citation

Paul Rosen and Voicu Popescu. Simplification of node position data for interactive visualization of dynamic datasets. IEEE Transactions on Visualization and Computer Graphics, 18:1537--1548, 2012. [ DOI ]

Bibtex


@article{Rosen.2011.TVCG,
  author = {Paul Rosen and Voicu Popescu},
  title = {Simplification of Node Position Data for Interactive Visualization
	of Dynamic Datasets},
  journal = {IEEE Transactions on Visualization and Computer Graphics},
  year = {2012},
  volume = {18},
  pages = {1537-1548},
  abstract = {We propose to aid the interactive visualization of time-varying spatial
	datasets by simplifying node position data over the entire simulation
	as opposed to over individual states. Our approach is based on two
	observations. The first observation is that the trajectory of some
	nodes can be approximated well without recording the position of
	the node for every state. The second observation is that there are
	groups of nodes whose motion from one state to the next can be approximated
	well with a single transformation. We present dataset simplification
	techniques that take advantage of this node data redundancy. Our
	techniques are general, supporting many types of simulations, they
	achieve good compression factors, and they allow rigorous control
	of the maximum node position approximation error. We demonstrate
	our approach in the context of finite element analysis data, of liquid
	flow simulation data, and of fusion simulation data.},
  address = {Los Alamitos, CA, USA},
  doi = {http://doi.ieeecomputersociety.org/10.1109/TVCG.2011.268},
  issn = {1077-2626},
  keywords = {simplification of node positions, trajectory simplification, trajectory
	clustering, rigid body decomposition, interactive visualization,
	simulation data compression},
  publisher = {IEEE Computer Society}
}