/Automatic Three-Dimensional Point Cloud Processing for Forest Inventory

Automatic Three-Dimensional Point Cloud Processing for Forest Inventory

Jean-Francois Lalonde, Nicolas Vandapel and Martial Hebert
Tech. Report, CMU-RI-TR-06-21, Robotics Institute, Carnegie Mellon University, July, 2006

Download Publication (PDF)

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author’s copyright. These works may not be reposted without the explicit permission of the copyright holder.


In this paper, we propose an approach that enables automatic, fast and accurate tree trunks segmentation from three-dimensional (3-D) laser data. Results have been demonstrated in real-time on-board a ground mobile robot. In addition, we propose an approach to estimate tree diameter at breast height (dbh) that was tested off-line on a variety of ground laser scanner data. Results are also presented for detection of tree trunks in aerial laser data. The underlying techniques using in all cases rely on 3-D geometry analysis of point clouds and geometric primitives fitting.

BibTeX Reference
author = {Jean-Francois Lalonde and Nicolas Vandapel and Martial Hebert},
title = {Automatic Three-Dimensional Point Cloud Processing for Forest Inventory},
year = {2006},
month = {July},
institution = {Carnegie Mellon University},
address = {Pittsburgh, PA},
number = {CMU-RI-TR-06-21},
keywords = {forest inventory, 3d point cloud, ladar, laser},