A model-based clustering method is proposed for clustering individuals on the basis of measurements taken over time. Data variability is taken into account through non-linear hier...
We present an improved statistical model of Poisson processes, with applications in photon-limited imaging. We build on previous work, adopting a multiscale representation of the ...
Stamatios Lefkimmiatis, George Papandreou, Petros ...
We present a simple, effective generalisation of variable order Markov
models to full online Bayesian estimation. The mechanism used is close
to that employed in context tree wei...
:We formulate structure from motion as a Bayesian inference problem, and use a Markov chain Monte Carlo sampler to sample the posterior on this problem. This results in a method th...
Tracking body poses of multiple persons in monocular video is a challenging problem due to the high dimensionality of the state space and issues such as inter-occlusion of the pers...