Simplification Of Node Position Data For Interactive Visualization Of Dynamic Data Sets

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.

Paul Rosen, and Voicu Popescu. Simplification Of Node Position Data For Interactive Visualization Of Dynamic Data Sets. IEEE Transactions on Visualization and Computer Graphics (TVCG), 2011.

@article{rosen2011simplification,
  title = {Simplification of Node Position Data for Interactive Visualization of Dynamic
    Data Sets},
  author = {Rosen, Paul and Popescu, Voicu},
  journal = {IEEE Transactions on Visualization and Computer Graphics (TVCG)},
  volume = {18},
  pages = {1537--1548},
  year = {2011},
  keywords = {simplification of node positions, trajectory simplification, trajectory
clustering, rigid body decomposition, interactive visualization,
simulation data compression},
  note = {textit{Presented at IEEE Visweek 2012.}},
  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.}
}