Most object tracking approaches either assume that the number of objects is constant, or that information about object existence is provided by some external source. Here, we show...
In thispaper, the problem ofsimultaneousmotionestimation of multiple independently moving objects is addressed. A novel Bayesian approach is designedfor solvingthisproblem using t...
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
In this paper we model the components of the compressive sensing (CS) problem using the Bayesian framework by utilizing a hierarchical form of the Laplace prior to model sparsity ...
S. Derin Babacan, Rafael Molina, Aggelos K. Katsag...
This paper reports our investigation on the problem of belief update in Bayesian networks (BN) using uncertain evidence. We focus on two types of uncertain evidences, virtual evid...