DocumentCode :
3529880
Title :
Robust real-time visual odometry for dense RGB-D mapping
Author :
Whelan, Thomas ; Johannsson, H. ; Kaess, Michael ; Leonard, John J. ; McDonald, John
Author_Institution :
Dept. of Comput. Sci., Nat. Univ. of Ireland Maynooth, Maynooth, Ireland
fYear :
2013
fDate :
6-10 May 2013
Firstpage :
5724
Lastpage :
5731
Abstract :
This paper describes extensions to the Kintinuous [1] algorithm for spatially extended KinectFusion, incorporating the following additions: (i) the integration of multiple 6DOF camera odometry estimation methods for robust tracking; (ii) a novel GPU-based implementation of an existing dense RGB-D visual odometry algorithm; (iii) advanced fused realtime surface coloring. These extensions are validated with extensive experimental results, both quantitative and qualitative, demonstrating the ability to build dense fully colored models of spatially extended environments for robotics and virtual reality applications while remaining robust against scenes with challenging sets of geometric and visual features.
Keywords :
SLAM (robots); cameras; distance measurement; image colour analysis; robot vision; GPU; Kintinuous algorithm; RGB-D camera pose tracking; SLAM pose-graph optimisation; advanced fused real-time surface coloring; dense RGB-D mapping; dense fully colored models; multiple 6DOF camera odometry estimation methods; robotics; robust real-time visual odometry; robust tracking; spatially extended KinectFusion; virtual reality applications; Cameras; Color; Graphics processing units; Image color analysis; Instruction sets; Iterative closest point algorithm; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation (ICRA), 2013 IEEE International Conference on
Conference_Location :
Karlsruhe
ISSN :
1050-4729
Print_ISBN :
978-1-4673-5641-1
Type :
conf
DOI :
10.1109/ICRA.2013.6631400
Filename :
6631400
Link To Document :
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