A probabilistic framework using dynamic Bayesian networks for human activity recognition and tracking

Bayesian inference in its simplest forms is the act of moving from sample data to generalisations with a measurable degree of certainty through the utilisation of probability theory generally and Bayes’ theorem specifically. Probabilistic Graphical Models (PGMs) on the other hand provide means to de...

Full description

Bibliographic Details

Main Author:	Mohamad Saada
Format:	Default Thesis
Published:	2021
Subjects:	Other information and computing sciences not elsewhere classified Dynamic Bayesian Networks Human Activity Recognition anomaly detection applications Multi-object tracking Flight simulator Information and Computing Sciences not elsewhere classified
Online Access:	https://dx.doi.org/10.26174/thesis.lboro.16895362.v1
Tags:	Add Tag No Tags, Be the first to tag this record!