Many low-level vision algorithms assume a prior probability over images, and there has been great interest in trying to learn this prior from examples. Since images are very non G...
Many recent techniques for low-level vision problems such as image denoising are formulated in terms of Markov random field (MRF) or conditional random field (CRF) models. Nonethel...
A fundamental vision driving pervasive computing research is access to personal and shared data anywhere at anytime. In many ways, this vision is close to being realized. Wireless...
We propose a method to control the luminance distribution on a scene by modeling the light propagation with direct and indirect components separately. To reduce the measurement tim...
We introduce an expandable Bayesian network (EBN) to handle the combination of diverse multiple homogeneous evidence sets. An EBN is an augmented Bayesian network which instantiat...