In the paper we combine a Bayesian Network model for encoding forensic evidence during a given time interval with a Hidden Markov Model (EBN-HMM) for tracking and predicting the de...
Olivier Y. de Vel, Nianjun Liu, Terry Caelli, Tib&...
Many techniques of knowledge-based segmentation consist of building statistical models that describe the deformations of the structure of interest, and then fit these models to t...
Charles Florin, Nikos Paragios, Gareth Funka-Lea, ...
As an extension of Bayesian network, module network is an appropriate model for inferring causal network of a mass of variables from insufficient evidences. However learning such ...
In this paper, a novel method to learn the intrinsic object structure for robust visual tracking is proposed. The basic assumption is that the parameterized object state lies on a...
— We consider the problem of finding sufficiently simple models of high-dimensional physical systems that are consistent with observed trajectories, and using these models to s...