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 :
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