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 | 1 | initial version |
Kd tree is pretty for Euclidean distance and clustering. The octree is more like the representation of space. Better for planning, and mapping.
Kdtree is more for sensor interpretation.
| | 2 | No.2 Revision |
Kd tree is pretty for Euclidean distance and clustering. The octree is more like the representation of space. Better for planning, and mapping.
Kdtree is more for sensor interpretation.
The octree separate your space in an symmetric manner while the cut but the Kdtree is more "chaotic"
If you put different data in different order inside a octree you get always the same three. By the Kdtree the structure change by the inserting order.
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