DocumentCode :
56793
Title :
Localized Registration of Point Clouds of Botanic Trees
Author :
Bucksch, A. ; Khoshelham, K.
Author_Institution :
Dept. of Geosci. & Remote Sensing, Delft Univ. of Technol., Delft, Netherlands
Volume :
10
Issue :
3
fYear :
2013
fDate :
May-13
Firstpage :
631
Lastpage :
635
Abstract :
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.
Keywords :
forestry; geophysical image processing; geophysical techniques; image registration; measurement by laser beam; remote sensing by laser beam; vegetation; botanic tree point clouds; branch segments; fine branch registration; global registration; local transformation parameters; localized point cloud registration; roughly registered point clouds; skeletonization method; tree dendrometric characteristics; Clouds; Estimation; Lasers; Octrees; Remote sensing; Skeleton; Vegetation; Automation; forestry; image registration; laser scanning; least squares; parameter estimation; skeletonization;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
Publisher :
ieee
ISSN :
1545-598X
Type :
jour
DOI :
10.1109/LGRS.2012.2216251
Filename :
6331508
Link To Document :
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