Author
Erdem, Tanju, Ercan, Ali Özer
Publication Date
2015-02
Publication Place
-
IEEE
Subject
Inertial sensor fusion, Extended Kalman filter, 3D camera tracking, inertial measurement unit, Accelerometer, Gyroscope
Type
Periodical
Language
English
Digital
Yes
Manuscript
No
Library
Özyeğin University
Library Asset ID
1057-7149
Record ID
e9c60303-0810-44a0-877d-6146c663f85c
Library Location
Electrical & Electronics Engineering, Computer Science
Date
2015-02
Notes
Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text
In a setup where camera measurements are used to estimate 3D egomotion in an extended Kalman filter (EKF) framework, it is well-known that inertial sensors (i.e., accelerometers and gyroscopes) are especially useful when the camera undergoes fast motion. Inertial sensor data can be fused at the EKF with the camera measurements in either the correction stage (as measurement inputs) or the prediction stage (as control inputs). In general, only one type of inertial sensor is employed in the EKF in the literature, or when both are employed they are both fused in the same stage. In this paper, we provide an extensive performance comparison of every possible combination of fusing accelerometer and gyroscope data as control or measurement inputs using the same data set collected at different motion speeds. In particular, we compare the performances of different approaches based on 3D pose errors, in addition to camera reprojection errors commonly found in the literature, which provides further insight into the strengths and weaknesses of different approaches. We show using both simulated and real data that it is always better to fuse both sensors in the measurement stage and that in particular, accelerometer helps more with the 3D position tracking accuracy, whereas gyroscope helps more with the 3D orientation tracking accuracy. We also propose a simulated data generation method, which is beneficial for the design and validation of tracking algorithms involving both camera and inertial measurement unit measurements in general.
DOI
10.1109/TIP.2014.2380176
Cilt
24
