@conference {1967, title = {Automated point cloud correspondence detection for underwater mapping using AUVs}, booktitle = {OCEANS 2015}, year = {2015}, month = {10/2015}, pages = {1-7}, publisher = {MTS}, organization = {MTS}, address = {Washington DC}, keywords = {accumulated 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}, isbn = {978-0-9339-5743-5}, author = {M. Hammond and A. Clark and A. Mahajan and S. Sharma and S. Rock} }