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Automated point cloud correspondence detection for underwater mapping using AUVs

Home » Publications » Automated point cloud correspondence detection for underwater mapping using AUVs
TitleAutomated point cloud correspondence detection for underwater mapping using AUVs
Publication TypeConference Paper
Year of Publication2015
AuthorsHammond, M., A. Clark, A. Mahajan, S. Sharma, and S. Rock
Conference NameOCEANS 2015
Date Published10/2015
PublisherMTS
Conference LocationWashington DC
ISBN Number978-0-9339-5743-5
Keywordsaccumulated navigation error estimation, automated point cloud correspondence detection, autonomous underwater vehicles, AUV, California, Computer Vision, computer vision literature, false positive matches, Feature extraction, ICP registration algorithm, image matching, image registration, inertial navigation, Iterative closest point algorithm, iterative closest point registration algorithm, iterative methods, less conservative matching criteria, marine radar, Monterey Bay, multibeam sonar data, multiple overlapping, point cloud alignment technique, pseudoimage keypoint extraction, pseudoimage keypoint labelling, pseudoimage keypoint matching, RANSAC, self-consistent map, sonar imaging, Sonar measurements, Sonar navigation, Three-dimensional displays, underwater canyon, underwater mapping, vehicle trajectory information, Vehicles, zero false positives
Refereed DesignationUnknown

Last modified Thu, 1 Sep, 2016 at 14:30

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