We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
Tracking humans in an indoor environment is an essential part of surveillance systems. Vision based and microphone array based trackers have been extensively researched in the pas...
Shankar T. Shivappa, Mohan M. Trivedi, Bhaskar D. ...
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...
Inferring users' actions and intentions forms an integral part of design and development of any human-computer interface. The presence of noisy and at times ambiguous sensory ...
Design and development of novel human-computer interfaces poses a challenging problem: actions and intentions of users have to be inferred from sequences of noisy and ambiguous mu...
Vladimir Pavlovic, James M. Rehg, Ashutosh Garg, T...