4261860
doi
10.5281/zenodo.4261860
oai:zenodo.org:4261860
user-eu
Alberto Ortiz
University of the Balearic Islands
Combination of Planes and Image Edges for a Visual Odometer for Weakly Textured Structured Environments
Joan P. Company-Corcoles
University of the Balearic Islands
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
RGB-D
visual odometry
weakly-textured environment (WTE)
<p>Camera trajectory estimation has generated a lot of interest during the last decades, especially for robotic positioning. It is well-known that outdoors positioning mainly relies on GPS, whereas one of the main used methods in indoor positioning is visual odometry. As it is well known, visual odometers get typically in trouble when the environment is weakly textured. Facing this situation, this paper develops and tests a novel visual odometer that combines image edges and planar information to estimate the trajectory of an RGB-D camera in environments that lack texture. We also present a plane matching method based on a graph matching technique. To conclude, a comparison of the proposed odometer for two well-known datasets and other visual odometers and SLAM systems is reported. The comparison shows our method as more accurate as for the estimation of the position in indoor places where visual features are poor, while similar values are obtained for other indoor environments.</p>
This is a preprint version of publication with DOI: https://doi.org/10.1109/ETFA.2019.8868237. This work is also supported by projects PGC2018-095709-B-C21 (MCIU/AEI/FEDER, UE) and PROCOE/4/2017 (Govern Balear, 50% P.O. FEDER 2014-2020 Illes Balears), and the scholarship BES-2015-071804.
Zenodo
2019-09-12
info:eu-repo/semantics/conferencePaper
4261859
user-eu
award_title=Robotics Technology for Inspection of Ships; award_number=779776; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/779776; funder_id=00k4n6c32; funder_name=European Commission;
1604881625.5923
636750
md5:91493e249a1fb9c2cde27881de7bd04a
https://zenodo.org/records/4261860/files/ETFA2019_Company_.pdf
public
10.5281/zenodo.4261859
isVersionOf
doi