Generative Multimedia (GM) applications are an increasingly popular way to
implement interactive media performances.
Our contributions include creating a metric for evaluating Generative
Multimedia performances, designing a model for accepting perceiver
preferences, and using those preferences to adapt GM performances.
The metric used is imprecision, which is the ratio of the
actual computation time of a GM element to the computation time of a
complete version of that GM element.
By taking a perceiver's
preferences into account when making adaptation decisions, applications
can produce
GM performances that meet soft real-time
and resource constraints while allocating imprecision to the GM elements
the perceiver least cares about.
Compared to other approaches, perceiver-directed imprecision best allocates
impreciseness while minimizing delay.Ph.D.Committee Chair: Schwan, Karsten; Committee Member: Ahamad, Mustaque; Committee Member: Howe, W. Gerry; Committee Member: Ramachandran, Kishore; Committee Member: Yalamanchili, Sudhaka
