In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
Modern live cell fluorescence microscopy imaging systems, used abundantly for studying intra-cellular processes in vivo, generate vast amounts of noisy image data that cannot be pr...
We introduce a new class of probabilistic latent variable model called the Implicit Mixture of Conditional Restricted Boltzmann Machines (imCRBM) for use in human pose tracking. K...
Graham Taylor, Leonid Sigal, David Fleet, Geoffrey...
In this paper, two multimodal systems for the tracking of multiple users in smart environments are presented. The first is a multiview particle filter tracker using foreground, c...
We present an algorithm for the layered segmentation of video data in multiple views. The approach is based on computing the parameters of a layered representation of the scene in...