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...
This work is motivated by the necessity to automate the discovery of structure in vast and evergrowing collection of relational data commonly represented as graphs, for example ge...
Sampling is an important tool for estimating large, complex sums and integrals over highdimensional spaces. For instance, importance sampling has been used as an alternative to ex...
Temporal Constraint Satisfaction Problems (TCSP) is a well known approach for representing and processing temporal knowledge. Important properties of the knowledge can be inferred...
This paper is concerned with how collaborative virtual environments can be structured in order to enable greater scalability and yet maintain a richness of communication. Based on...