A new information-theoretic approach is presented for finding the pose of an object in an image. The technique does not require information about the surface properties of the ob...
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
A new model for the multiscale characterization of turbulence and chaotic information in digital images is presented. The model is applied to infrared satellite images for the det...
In this paper, we present an automatic classification framework combining appearance based features and Hidden Markov Models (HMM) to detect unusual events in image sequences. One...
We propose a generative model that codes the geometry and appearance of generic visual object categories as a loose hierarchy of parts, with probabilistic spatial relations linkin...