The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
Asma Rabaoui, Nicolas Viandier, Juliette Marais, E...
This paper presents a motion estimation and segmentation algorithm based on multiple parametric model estimation that determines the a priori unknown number of motion models prese...
Data on the Web is increasingly being used for discovery and exploratory tasks. Unlike traditional fact-finding tasks that require only the typical single-query and response parad...
Abstract—We introduce an extended family of continuous-domain stochastic models for sparse, piecewise-smooth signals. These are specified as solutions of stochastic differential...
Data modeling is an essential part of the software development process, and together with application modeling forms the core of the model-driven approach to software engineering....