By Topic

Localized Registration of Point Clouds of Botanic Trees

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
$33 $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

2 Author(s)
Alexander Bucksch ; School of Interactive Computing and the School of Biology, Georgia Institute of Technology, Atlanta, GA, USA ; Kourosh Khoshelham

A global registration is often insufficient for estimating dendrometric characteristics of trees because individual branches of the same tree may exhibit different positions between two scanning procedures. Therefore, we introduce a localized approach to register point clouds of botanic trees. Given two roughly registered point clouds PC1 and PC2 of a tree, we apply a skeletonization method to both point clouds. Based on these two skeletons, initial correspondences between branch segments of both point clouds are established to estimate local transformation parameters. The transformation estimation relies on minimizing the distance between the points in PC1 and the skeleton of PC2. The performance of the method is demonstrated on two example trees. It is shown that significant improvements can be achieved for the registration of fine branches. These improvements are quantified as the residual point-to-line distances before and after the localized fine registration. In our experiment, the residual error after the local registration is on an average of 5 mm over 90 skeleton segments, which is about three times smaller than the average residual error of the initial rough registration.

Published in:

IEEE Geoscience and Remote Sensing Letters  (Volume:10 ,  Issue: 3 )