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


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Abstract
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.

Keywords
forest inventory, 3d point cloud, ladar, laser

Notes
Associated Center(s) / Consortia: Vision and Autonomous Systems Center and Field Robotics Center
Associated Project(s): CTA Robotics
Number of pages: 22

Text Reference
Jean-Francois Lalonde, Nicolas Vandapel, and Martial Hebert, "Automatic Three-Dimensional Point Cloud Processing for Forest Inventory," tech. report CMU-RI-TR-06-21, Robotics Institute, Carnegie Mellon University, July, 2006

BibTeX Reference
@techreport{Lalonde_2006_5480,
   author = "Jean-Francois Lalonde and Nicolas Vandapel and Martial Hebert",
   title = "Automatic Three-Dimensional Point Cloud Processing for Forest Inventory",
   booktitle = "",
   institution = "Robotics Institute",
   month = "July",
   year = "2006",
   number= "CMU-RI-TR-06-21",
   address= "Pittsburgh, PA",
}