A Bayesian marked point process (MPP) model is developed
to detect and count people in crowded scenes. The
model couples a spatial stochastic process governing number
and placem...
This paper proposes a Bayesian approach for estimation of instrument parameter in convex image deconvolution. The parameters of the instrument response (PSF) are jointly estimated...
Adaptor grammars extend probabilistic context-free grammars to define prior distributions over trees with "rich get richer" dynamics. Inference for adaptor grammars seek...
Many probabilistic models introduce strong dependencies between variables using a latent multivariate Gaussian distribution or a Gaussian process. We present a new Markov chain Mo...
Iain Murray, Ryan Prescott Adams, David J. C. MacK...
We propose a novel tracking framework called visual tracker sampler that tracks a target robustly by searching for the appropriate trackers in each frame. Since the real-world trac...