Given the growth in application-specific processors, there is a strong need for a retargetable modeling framework that is capable of accurately capturing complex processor behavi...
Model-based clustering of motion trajectories can be posed as the problem of learning an underlying mixture density function whose components correspond to motion classes with dif...
We study models that characterize pen trajectories of online handwritten characters in a fine manner. We propose radical based fine trajectory hidden Markov models (HMMs), which...
: To model surface imperfections and weathering, we proposea two-step texture generation framework in between manual texture synthesis and automatic physical simulation. Although t...
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...