DocumentCode
2010953
Title
Robust egomotion for large-scale trajectories
Author
Rodriguez, Diego ; Aouf, Nabil
Author_Institution
Dept. of Inf. & Syst. Eng. (DISE), Cranfield Univ., Shrivenham, UK
fYear
2012
fDate
13-15 Sept. 2012
Firstpage
156
Lastpage
161
Abstract
This paper presents an effective egomotion solution based on high curvature image features described using local intensity histograms for stereo matching and tracking. To robustify the visual processing system, we propose feature extraction over moment image representation to overcome the adverse effects of illumination changes. A bundle adjustment optimisation technique, thoroughly analysed for different reprojection strategies, is developed for motion estimation of an autonomous platform. The quality of results is shown to be on par with high quality GPS-corrected-INS systems, even for long-range trajectories.
Keywords
feature extraction; image matching; image representation; motion estimation; optimisation; stereo image processing; autonomous platform; bundle adjustment optimisation technique; curvature image features; feature extraction; image representation; intensity histograms; large scale trajectories; robust egomotion; stereo matching; stereo tracking; visual processing system; Cameras; Cost function; Feature extraction; Motion estimation; Robustness; Tracking; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Multisensor Fusion and Integration for Intelligent Systems (MFI), 2012 IEEE Conference on
Conference_Location
Hamburg
Print_ISBN
978-1-4673-2510-3
Electronic_ISBN
978-1-4673-2511-0
Type
conf
DOI
10.1109/MFI.2012.6343049
Filename
6343049
Link To Document