On fractional models for human motion tracking

Abstract

In this work we present the construction and evaluation of recursive Bayesian estimation algorithms for human motion tracking using fractional order models. The presented schemes include both fixed fractional order as well as variable order models with implicit and explicit model order estimation schemes. The performance of the designed techniques is compared to a set of conventional integral order methods using several measurements of human hand and head motions.