This paper proposes a state based approach to gesture learning and recognition. Using spatial clustering and temporal alignment, each gesture is defined to be an ordered sequence ...
State-of-the-art machine translation techniques are still far from producing high quality translations. This drawback leads us to introduce an alternative approach to the translat...
Jorge Civera, Elsa Cubel, Antonio L. Lagarda, Davi...
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...
Currently, few tools are available for assisting developers with debugging intelligent systems. Because these systems rely heavily on context dependent knowledge and sometimes sto...
We present various techniques for improving the time and space efficiency of symbolic model checking for system requirements specified as synchronous finite state machines. We use...
William Chan, Richard J. Anderson, Paul Beame, Dav...