By Topic

Point cloud processing strategies for noise filtering, structural segmentation, and meshing of ground-based 3D Flash LIDAR images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Natale, D.J. ; Appl. Res. Lab., Pennsylvania State Univ., University Park, PA, USA ; Baran, M.S. ; Tutwiler, R.L.

It is now the case that well-performing flash LIDAR focal plane array devices are commercially available. Such devices give us the ability to measure and record frame-registered 3D point cloud sequences at video frame rates. For many 3D computer vision applications this allows the processes of structure from motion or multi-view stereo reconstruction to be circumvented. This allows us to construct simpler, more efficient, and more robust 3D computer vision systems. This is a particular advantage for ground-based vision tasks which necessitate real-time or near real-time operation. The goal of this work is introduce several important considerations for dealing with commercial 3D Flash LIDAR data and to describe useful strategies for noise filtering, structural segmentation, and meshing of ground-based data. With marginal refinement efforts the results of this work are directly applicable to many ground-based computer vision tasks.

Published in:

Applied Imagery Pattern Recognition Workshop (AIPR), 2010 IEEE 39th

Date of Conference:

13-15 Oct. 2010