Spatio-temporal data streams that are generated from mobile stream sources (e.g., mobile sensors) experience similar environmental conditions that result in distinct phenomena. Sev...
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
Latent Variable Models (LVM), like the Shared-GPLVM
and the Spectral Latent Variable Model, help mitigate over-
fitting when learning discriminative methods from small or
modera...
We use concepts from chaos theory in order to model
nonlinear dynamical systems that exhibit deterministic behavior.
Observed time series from such a system can be embedded
into...
We are developing a system to extract geodetic, textured CAD models from thousands of initially uncontrolled, close-range ground and aerial images of urban scenes. Here we describ...