Ioan Raicu

Illinois Institute of Technology

Argonne National Laboratory

Techniques for analysis and visualization of large-scale LIDAR scan data of urban environments

Patrick J. Flynn, CSE/EE, University of Notre Dame
Alexandri Zavodny, CSE, University of Notre Dame
Stuart Building 238
Tuesday, January 18th, 2011
11:30AM - 12:30PM

Abstract: Efficient LIDAR scanning technology has led to acquisition of very large 3D datasets for application areas such as terrain and urban modeling, archaeological preservation, city planning, and more. However, analysis and visualization of such data can be difficult due to its representation as a series of disconnected 3D points and due to increasing dataset sizes, which can consist of billions of points. In this talk, we will address a number of techniques we have developed with scalability in mind. For surface extraction, we utilize a multistage region-growing technique which allows us to process data subsets in parallel and which is robust to imprecise measurements. We will then address a framework for triangulation of the extracted structures which allows us to represent them as solid, textured meshes which are minimal in polygon and vertex count. We will show examples of these techniques on real-world datasets and discuss future directions for research.

Slides (PDF)

Patrick J. Flynn is Professor of Computer Science & Engineering and Concurrent Professor of Electrical Engineering at the University of Notre Dame. He received the Ph.D. in Computer Science (1990) from Michigan State University, East Lansing. His research interests include computer vision, biometrics, and image processing. Dr. Flynn is a Senior Member of IEEE and a Fellow of IAPR.

Alexandri Zavodny is a graduate student at the University of Notre Dame. He received his Master's degree from the University in 2010 in Computer Science, and is currently working toward a Ph.D. in the same field. His research focuses on analysis and visualization of large-scale LiDAR datasets, and his research interests extend to computer vision and computer graphics.