Point Cloud Library (PCL) 1.13.0
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/build/pcl-TSDloU/pcl-1.13.0+dfsg/octree/octree.doxy
1/**
2 \addtogroup octree Module octree
3
4 \section secOctreePresentation Overview
5
6The <b>pcl_octree</b> library provides efficient methods for creating a hierarchical tree
7data structure from point cloud data. This enables spatial partitioning,
8downsampling and search operations on the point data set.
9Each octree node has either eight children or no children. The root node describes
10a cubic bounding box which encapsulates all points. At every tree level, this space
11becomes subdivided by a factor of 2 which results in an increased voxel resolution.
12
13The <b>pcl_octree</b> implementation provides efficient nearest neighbor search routines,
14such as "Neighbors within Voxel Search”, “K Nearest Neighbor Search” and
15“Neighbors within Radius Search”. It automatically adjusts its dimension to the point
16data set. A set of leaf node classes provide additional functionality, such as
17spacial "occupancy" and "point density per voxel" checks. Functions for serialization
18and deserialization enable to efficiently encode the octree structure into a binary format.
19Furthermore, a memory pool implementation reduces expensive memory allocation and
20deallocation operations in scenarios where octrees needs to be created at high rate.
21
22The following figure illustrates the voxel bounding boxes of an octree nodes at lowest tree level.
23The octree voxels are surrounding every 3D point from the bunny's surface. The red dots represent the point data.
24This image is created with the octree_viewer (visualization/tools/octree_viewer).
25
26For examples how to use the <b>pcl_octree</b> library, please visit the <a href="http://www.pointclouds.org/documentation/tutorials/">pcl tutorial page</a>.
27
28\image html http://www.pointclouds.org/assets/images/contents/documentation/octree_bunny.png
29
30
31 \section secOctreeRequirements Requirements
32 - \ref common "common"
33
34*/