Using Visualization and Animation to Convey Motion in Experimental
Data
Abstract
Computer visualization is a valuable technique for
understanding massive amounts of data. By providing faithful
and efficient depiction of the underlying phenomena,
computer visualization makes it possible for scientists
to take advantage of faster parallel
computers and advanced experimental techniques.
This thesis uses static visualization and computer animation
to provide graphical explanations for a pattern forming system
produced from a combustion experiment.
Like any other system, pattern forming systems must be properly
formulated and modeled in order to be visualized.
The original data is recorded on videotapes,
preprocessed into individual raster frames and stored in a directory.
Tracking is then conducted on the frames, and quantified
information for individual objects is generated as
the starting point of the visualizations.
Two criteria are developed as a basis of data modeling:
a minimum area invariant and the principal representation
of image object.
The static visualizations model the data to take advantage of
the ParaGraph visualization tool which is designed for monitoring
the performance of parallel programs. The data is processed
so that it has state information in the form of ParaGraph
input format (PICL). Static visualizations are
useful for summarizing state information over time or space,
but they lack the sense of motion. Computer animation gives the
impression of motion by adding time control to visualizations.
The animation programs are based on the POLKA animation library.
The static visualization and computer animation techniques are
conducted on three modes of the flame system---hopping, rotating,
and radial extinction. Each of these modes again has
several submodes. The visualizations provide insights
which were not available from direct viewing of the tape.