We devise and experiment with a dynamical kernel-based system for tracking hand movements from neural activity. The state of the system corresponds to the hand location, velocity,...
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
Ivo Couckuyt, Dirk Gorissen, Hamed Rouhani, Eric L...
This paper uses Factored Latent Analysis (FLA) to learn a factorized, segmental representation for observations of tracked objects over time. Factored Latent Analysis is latent cl...
We propose a space-time Markov Random Field (MRF)
model to detect abnormal activities in video. The nodes in
the MRF graph correspond to a grid of local regions in the
video fra...
Jaechul Kim (University of Texas at Austin), Krist...
We present the use of layered probabilistic representations for modeling human activities, and describe how we use the representation to do sensing, learning, and inference at mul...