@inproceedings{12bd527e7d5647f2ba51a2e8ababcf8c,
title = "Robust visual odometry in underwater environment",
abstract = "The accurate estimation of pose and velocity of an autonomous underwater vehicle (AUV) is critical to ensure the repeatability and validity of scientific data that is captured using sensors onboard the AUV. A low-cost and effective way is by using stereo camera sensors to perform visual odometry (VO). However, this is a difficult problem in underwater due to poor imaging condition and inconsistent motion caused by water flow. This paper proposes a robust and effective stereo underwater VO system that can overcome aforementioned difficulties and accurately localize the AUV. Experimental results demonstrate that the proposed pipeline outperforms existing VO systems in underwater environment, as well as obtains a comparative performance on the KITTI benchmark dataset.",
author = "Jun Zhang and Viorela Ila and Laurent Kneip",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018 ; Conference date: 28-05-2018 Through 31-05-2018",
year = "2018",
month = dec,
day = "4",
doi = "10.1109/OCEANSKOBE.2018.8559452",
language = "English",
series = "2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 OCEANS - MTS/IEEE Kobe Techno-Oceans, OCEANS - Kobe 2018",
address = "United States",
}