%0 Conference Paper %1 kreylos2008immersive %A Kreylos, Oliver %A Bawden, Gerald W. %A Kellogg, Louise H. %B Advances in Visual Computing %C Berlin, Heidelberg %D 2008 %E Bebis, George %E Boyle, Richard %E Parvin, Bahram %E Koracin, Darko %E Remagnino, Paolo %E Porikli, Fatih %E Peters, Jörg %E Klosowski, James %E Arns, Laura %E Chun, Yu Ka %E Rhyne, Theresa-Marie %E Monroe, Laura %I Springer Berlin Heidelberg %K pointclouds visualization %P 846--855 %T Immersive Visualization and Analysis of LiDAR Data %X We describe an immersive visualization application for point cloud data gathered by LiDAR (Light Detection And Ranging) scanners. LiDAR is used by geophysicists and engineers to make highly accurate measurements of the landscape for study of natural hazards such as floods and earthquakes. The large point cloud data sets provided by LiDAR scans create a significant technical challenge for visualizing, assessing, and interpreting these data. Our system uses an out-of-core view-dependent multiresolution rendering scheme that supports rendering of data sets containing billions of 3D points at the frame rates required for immersion (48--60 fps). The visualization system is the foundation for several interactive analysis tools for quality control, extraction of survey measurements, and the extraction of isolated point cloud features. The software is used extensively by researchers at the UC Davis Department of Geology and the U.S. Geological Survey, who report that it offers several significant advantages over other analysis methods for the same type of data, especially when used in an immersive visualization environment such as a CAVE. %@ 978-3-540-89639-5

@inproceedings{kreylos2008immersive, abstract = {We describe an immersive visualization application for point cloud data gathered by LiDAR (Light Detection And Ranging) scanners. LiDAR is used by geophysicists and engineers to make highly accurate measurements of the landscape for study of natural hazards such as floods and earthquakes. The large point cloud data sets provided by LiDAR scans create a significant technical challenge for visualizing, assessing, and interpreting these data. Our system uses an out-of-core view-dependent multiresolution rendering scheme that supports rendering of data sets containing billions of 3D points at the frame rates required for immersion (48--60 fps). The visualization system is the foundation for several interactive analysis tools for quality control, extraction of survey measurements, and the extraction of isolated point cloud features. The software is used extensively by researchers at the UC Davis Department of Geology and the U.S. Geological Survey, who report that it offers several significant advantages over other analysis methods for the same type of data, especially when used in an immersive visualization environment such as a CAVE.}, added-at = {2022-12-09T12:09:40.000+0100}, address = {Berlin, Heidelberg}, author = {Kreylos, Oliver and Bawden, Gerald W. and Kellogg, Louise H.}, biburl = {https://www.bibsonomy.org/bibtex/291e7f3255489282966d0fd54e3bfdb93/abernstetter}, booktitle = {Advances in Visual Computing}, editor = {Bebis, George and Boyle, Richard and Parvin, Bahram and Koracin, Darko and Remagnino, Paolo and Porikli, Fatih and Peters, J{\"o}rg and Klosowski, James and Arns, Laura and Chun, Yu Ka and Rhyne, Theresa-Marie and Monroe, Laura}, interhash = {0eb39568fde72fa6210214b93a82f03c}, intrahash = {91e7f3255489282966d0fd54e3bfdb93}, isbn = {978-3-540-89639-5}, keywords = {pointclouds visualization}, pages = {846--855}, publisher = {Springer Berlin Heidelberg}, timestamp = {2022-12-09T12:09:40.000+0100}, title = {Immersive Visualization and Analysis of LiDAR Data}, year = 2008 }