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On sensor fusion for head tracking in augmented reality applications

Title	On sensor fusion for head tracking in augmented reality applications
Author	Ercan, Ali Özer, Erdem, Tanju
Publication Date:	2011
Publication Place	- IEEE
Subject	Augmented reality
Type	Document
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	978-1-4577-0081-1
Record ID	e6f87a41-7bbe-4730-8572-f27f4492b07b
Library Location	Electrical & Electronics Engineering, Computer Science
Date	2011
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	The paper presents a simple setup consisting of a camera and an accelerometer located on a head mounted display, and investigates the performance of head tracking for augmented reality applications using this setup. The information from the visual and inertial sensors is fused in an extended Kalman filter (EKF) tracker. The performance of treating accelerometer measurements as control inputs is compared to treating both camera and accelerometer measurements as measurements, i.e., fusing them in the measurement update stage of the EKF simultaneously. It is concluded via simulations that treating accelerometer measurements as control inputs performs practically as good as treating both measurements as measurements, while providing a lower complexity tracker.

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Özyeğin University

On sensor fusion for head tracking in augmented reality applications

Author Ercan, Ali Özer, Erdem, Tanju

Publication Date 2011

Publication Place - IEEE

Subject Augmented reality

Type Document

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 978-1-4577-0081-1

Record ID e6f87a41-7bbe-4730-8572-f27f4492b07b

Library Location Electrical & Electronics Engineering, Computer Science

Date 2011

Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Sample Text The paper presents a simple setup consisting of a camera and an accelerometer located on a head mounted display, and investigates the performance of head tracking for augmented reality applications using this setup. The information from the visual and inertial sensors is fused in an extended Kalman filter (EKF) tracker. The performance of treating accelerometer measurements as control inputs is compared to treating both camera and accelerometer measurements as measurements, i.e., fusing them in the measurement update stage of the EKF simultaneously. It is concluded via simulations that treating accelerometer measurements as control inputs performs practically as good as treating both measurements as measurements, while providing a lower complexity tracker.