In this work, we propose an unsupervised Bayesian model for the detection of moving objects from dynamic scenes. This unsupervised solution is a three-step approach that uses a st...
We address the problem of Bayesian image reconstruction with a prior that captures the notion of a clustered intensity histogram. The problem is formulated in the framework of a j...
The Gaussian mixture model is a powerful statistical tool in data modeling and analysis. Generally, the EM algorithm is utilized to learn the parameters of the Gaussian mixture. Ho...
Multiview video is increasingly getting attention due to emerging applications such as 3DTV and immersive teleconferencing. In this paper, we present a non-stationary Hidden Marko...
Lorenzo Rossi, Jacob Chakareski, Pascal Frossard, ...
Background: Progressive advances in the measurement of complex multifactorial components of biological processes involving both spatial and temporal domains have made it difficult...