Probabilistic Tracking of Pedestrian Movements via In-Floor Force Sensing

Author

Rajalingham, Rishi ; Visell, Yon ; Cooperstock, Jeremy R.

Author_Institution

Centre for Intell. Machines, McGill Univ., Montreal, QC, Canada

fYear

2010

fDate

May 31 2010-June 2 2010

Firstpage

143

Lastpage

150

Abstract

This article presents a probabilistic approach to the tracking and estimation of the lower body posture of users moving on foot over an instrumented floor surface. The latter consists of an array of low-cost force platforms providing intermittent foot-floor contact data with limited spatial resolution. We use this data to track body posture in 3D space using Bayesian filters with a switching state-space model. Potential applications of this work to person tracking and human-computer interaction are described.

Keywords

filtering theory; human computer interaction; image resolution; motion estimation; probability; Bayesian filters; body posture tracking; foot-floor contact data; human-computer interaction; in-floor force sensing; instrumented floor surface; pedestrian movement tracking; probabilistic tracking; spatial resolution; switching state-space model; Bayesian methods; Computer vision; Filtering; Force sensors; Humans; Instruments; Kinematics; Sensor arrays; Tiles; Tracking; in-floor sensing; kinematic tracking; particle filter;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Robot Vision (CRV), 2010 Canadian Conference on

Conference_Location

Ottawa, ON

Print_ISBN

978-1-4244-6963-5

Type

conf

DOI

10.1109/CRV.2010.26

Filename

5479476