Output details
15 - General Engineering
University of Oxford
Article title
An O(N(2)) square root unscented Kalman Filter for visual simultaneous localization and mapping.
Type
D - Journal article
Title of journal
IEEE Trans Pattern Anal Mach Intell
Article number
-
Volume number
31
Issue number
7
First page of article
1251
ISSN of journal
0162-8828
Year of publication
2009
Number of additional authors
2
Additional information
In 2007 the state of the art in real-time visual mapping was Davison's monoSLAM. During EPSRC project GR/S97774 “Wearable Visual Computing” we studied two drawbacks inherent in monoSLAM's use of the extended Kalman Filter, viz computational complexity and vulnerability to systemic non-linearity. The Unscented Kalman Filter handled non-linearity better, but its standard form exhibited cubic complexity in the number of scene points, higher than that of the EKF. By analysis of the underlying linear algebra, this paper showed that the UKF could also achieve quadratic complexity. The paper is chosen for its rigorous contribution to vision theory.
Interdisciplinary
-
Cross-referral requested
-
Research group
D - Information, Vision and Control
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
