In this paper we propose a generic framework based on Hidden Markov Models (HMMs) for recognition of individuals from their gait. The HMM framework is suitable, because the gait o...
Aravind Sundaresan, Amit K. Roy Chowdhury, Rama Ch...
We show how improved sequences for magnetic resonance imaging can be found through optimization of Bayesian design scores. Combining approximate Bayesian inference and natural ima...
Matthias W. Seeger, Hannes Nickisch, Rolf Pohmann,...
Modelling textured images as AM-FM functions has been applied during the last years to texture analysis and segmentation tasks. In this paper we present some advances in two direc...
Aiming at detecting secret information hidden in a given image using steganographic tools, steganalysis has been of interest since the end of 1990’s. In particular, universal ste...
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The appro...