The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008 
468 
this method depends on the number of points shown in the of LiDAR data, we could draw the scene within an acceptable 
screen, not the volume of data, that is, regardless of the amount time. 
with display precision 
with display precision 
and screen buffer 
Sum of Points 
Render time(ms) 
Sum of Points 
Render time(ms) 
109785 
3183.41 
38415 
3293.98 
49468 
1617.26 
14467 
1646.21 
20202 
759.041 
4259 
769.161 
7743 
316.376 
1207 
320.897 
2700 
118.496 
321 
120.296 
992 
47.2825 
85 
46.4422 
259 
11.6568 
21 
12.4862 
123 
5.55098 
11 
5.99378 
17 
0.800381 
4 
0.850667 
1 
0.0798984 
1 
0.0804572 
Table. 1. The parameter in the ways of taking 1.5 pixel precision, and 1.5 pixel precision with screen buffer: 
6. CONCLUSION 
This paper discusses several aspects in managing and 
displaying LiDAR data, i.e., data partition using octree, 
building local KD trees, improving the KD node, and 
accelerating display of very large LiDAR data. Experiments 
show that the approach is particularly efficient for very dense 
points or points far away from the view point. The display time 
for the whole scene no longer relies on the volume of data, but 
on the amount of points shown on screen. Nevertheless, KD 
tree hasn’t the ability to insert or delete data dynamically. More 
efforts are needed for our methods to process LiDAR data more 
dynamically. 
Acknowledgement: The research is funded by the Chinese 
National High-tech R&D Program (863 Program: 
2006AA12Z151). 
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