}. Istanbul 2004
1e ground lidar
9.b containing
results after the
ults of merged
ity respectively.
ies of the stairs
. Wall and roof
Qo.
(f)
Fig . 9. Ground lidar example (a) point cloud (b) results after
split (c) results after merge (d) classify by area (e) classify by
Gradient (f) classify by average intensity
24.27 sec.
360.96 sec.
Number of the total octree layers 10
Computation time for split process
Computation time for merge process
Number of the total leave nodes 19803
Extracted planes and % of the total points used | 10944, 98.7%
Number of nodes have less than 3 points 4323
Table 3. Ground laserscan information
5. CONCLUSIONS
Sub-randomly distributed point cloud of lidar data needs an ad
hoc segmentation method for the extraction of spatial
information. This paper proposes an octree-based split-and-
merge segmentation method to divide lidar data into clusters of
3D planes and can apply to bath airborne and ground lidar data.
The thresholds designed in the algorithm can be adjusted to fit
different data sets. We expect this segmentation method can be
à stepping stone and applying to the other application of lidar
data. For example:
e 3D Feature extraction and coordinate measurement ---
3D spatial geometric properties (line and point)can be
explore by intersection of the extracted 3D planes.
e Building reconstruction --- extracted 3D features can be
analysis to reconstruct the building models.
e Classification — Attributes derived from 3D planes can be
used to classify different meaningful information of
planes.
e Data filtering and compression --- points were not used
to form planes can be filtered out and densely distributed
on a plane can be express by the 4 plane parameters and
boundary to reduce data size.
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B3. Istanbul 2004
Further study is needed to improvement and modification the
proposed method to fit various applications of both airborne and
ground based lidar data.
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ACKNOWLEDGEMENTS
The authors deeply appreciate the provision of the airborne
Lidar data by the Council of Agriculture, Executive Yuan, R. O.
C.
