Fast exact Bayesian inference for high-dimensional models

Autor: Ferreira, JF, Lanillos, P, Dias, J
Jazyk: angličtina
Rok vydání: 2015
Zdroj: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015), Hamburg, Germany, 28 September-2 October 2015
Popis: In this text, we present the principles that allow the tractable implementation of exact inference processes concerning a group of widespread classes of Bayesian generative models, which have until recently been deemed as intractable whenever formulated using high-dimensional joint distributions. We will demonstrate the usefulness of such a principled approach with an example of real-time OpenCL implementation using GPUs of a full-fledged, computer vision-based model to estimate gaze direction in human-robot interaction (HRI).
Databáze: OpenAIRE