A Quaternion-Based Motion Tracking and Gesture Recognition System Using Wireless Inertial Sensors

It appears your Web browser is not configured to display PDF files. Download adobe Acrobat or click here to download the PDF file.

Click here to download the PDF file.


Arsenault, Dennis




This work examines the development of a unified motion tracking and gesture recognition system that functions through worn inertial sensors. The system is comprised of a total of ten sensors and uses their quaternion output to map the player's motions to an onscreen character. To demonstrate the system's capabilities, a simple virtual reality game was created. A hierarchical skeletal model was implemented that allows players to navigate the virtual world without the need of a hand-held controller. In addition to motion tracking, the system was tested for its potential for gesture recognition. Despite the widespread use of Hidden Markov Models, our modified Markov Chain algorithm obtained higher average recognition accuracies at 95% and faster computation times. Combining motion tracking and dynamic gesture recognition into a single unified system is unique in the literature and comes at a time when virtual reality and wearable computing are emerging in the marketplace.


Computer Science




Carleton University

Thesis Degree Name: 

Master of Applied Science: 

Thesis Degree Level: 


Thesis Degree Discipline: 

Human-Computer Interaction

Parent Collection: 

Theses and Dissertations

Items in CURVE are protected by copyright, with all rights reserved, unless otherwise indicated. They are made available with permission from the author(s).