OpenCV  5.0.0-pre
Open Source Computer Vision
Loading...
Searching...
No Matches
Public Member Functions | Static Public Member Functions | Protected Attributes | List of all members
cv::Octree Class Reference

Octree for 3D vision. More...

#include <opencv2/3d.hpp>

Collaboration diagram for cv::Octree:

Public Member Functions

 Octree ()
 Default constructor.
 
 ~Octree ()
 Default destructor.
 
void clear ()
 Reset all octree parameter.
 
bool deletePoint (const Point3f &point)
 Delete a given point from the Octree.
 
bool empty () const
 returns true if the rootnode is NULL.
 
void getPointCloudByOctree (OutputArray restoredPointCloud, OutputArray restoredColor=noArray())
 restore point cloud data from Octree.
 
bool insertPoint (const Point3f &point, const Point3f &color={ })
 Insert a point data with color to a OctreeNode.
 
bool isPointInBound (const Point3f &point) const
 Determine whether the point is within the space range of the specific cube.
 
void KNNSearch (const Point3f &query, const int K, OutputArray points, OutputArray colors, OutputArray squareDists) const
 K Nearest Neighbor Search in Octree.
 
void KNNSearch (const Point3f &query, const int K, OutputArray points, OutputArray squareDists=noArray()) const
 K Nearest Neighbor Search in Octree.
 
int radiusNNSearch (const Point3f &query, float radius, OutputArray points, OutputArray colors, OutputArray squareDists) const
 Radius Nearest Neighbor Search in Octree.
 
int radiusNNSearch (const Point3f &query, float radius, OutputArray points, OutputArray squareDists=noArray()) const
 Radius Nearest Neighbor Search in Octree.
 

Static Public Member Functions

static Ptr< OctreecreateWithDepth (int maxDepth, double size, const Point3f &origin={ }, bool withColors=false)
 Creates an empty Octree with given maximum depth.
 
static Ptr< OctreecreateWithDepth (int maxDepth, InputArray pointCloud, InputArray colors=noArray())
 Create an Octree from the PointCloud data with the specific maxDepth.
 
static Ptr< OctreecreateWithResolution (double resolution, double size, const Point3f &origin={ }, bool withColors=false)
 Creates an empty Octree with given resolution.
 
static Ptr< OctreecreateWithResolution (double resolution, InputArray pointCloud, InputArray colors=noArray())
 Create an Octree from the PointCloud data with the specific resolution.
 

Protected Attributes

Ptr< Impl > p
 

Detailed Description

Octree for 3D vision.

In 3D vision filed, the Octree is used to process and accelerate the pointcloud data. The class Octree represents the Octree data structure. Each Octree will have a fixed depth. The depth of Octree refers to the distance from the root node to the leaf node.All OctreeNodes will not exceed this depth.Increasing the depth will increase the amount of calculation exponentially. And the small number of depth refers low resolution of Octree. Each node contains 8 children, which are used to divide the space cube into eight parts. Each octree node represents a cube. And these eight children will have a fixed order, the order is described as follows:

For illustration, assume,

rootNode: origin == (0, 0, 0), size == 2

Then,

children[0]: origin == (0, 0, 0), size == 1

children[1]: origin == (1, 0, 0), size == 1, along X-axis next to child 0

children[2]: origin == (0, 1, 0), size == 1, along Y-axis next to child 0

children[3]: origin == (1, 1, 0), size == 1, in X-Y plane

children[4]: origin == (0, 0, 1), size == 1, along Z-axis next to child 0

children[5]: origin == (1, 0, 1), size == 1, in X-Z plane

children[6]: origin == (0, 1, 1), size == 1, in Y-Z plane

children[7]: origin == (1, 1, 1), size == 1, furthest from child 0

Constructor & Destructor Documentation

◆ Octree()

cv::Octree::Octree ( )

Default constructor.

◆ ~Octree()

cv::Octree::~Octree ( )

Default destructor.

Member Function Documentation

◆ clear()

void cv::Octree::clear ( )
Python:
cv.Octree.clear() -> None

Reset all octree parameter.

Clear all the nodes of the octree and initialize the parameters.

◆ createWithDepth() [1/2]

static Ptr< Octree > cv::Octree::createWithDepth ( int  maxDepth,
double  size,
const Point3f origin = { },
bool  withColors = false 
)
static
Python:
cv.Octree.createWithDepth(maxDepth, size[, origin[, withColors]]) -> retval
cv.Octree.createWithDepth(maxDepth, pointCloud[, colors]) -> retval
cv.Octree_createWithDepth(maxDepth, size[, origin[, withColors]]) -> retval
cv.Octree_createWithDepth(maxDepth, pointCloud[, colors]) -> retval

Creates an empty Octree with given maximum depth.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters
maxDepthThe max depth of the Octree
sizebounding box size for the Octree
originInitial center coordinate
withColorsWhether to keep per-point colors or not
Returns
resulting Octree

◆ createWithDepth() [2/2]

static Ptr< Octree > cv::Octree::createWithDepth ( int  maxDepth,
InputArray  pointCloud,
InputArray  colors = noArray() 
)
static
Python:
cv.Octree.createWithDepth(maxDepth, size[, origin[, withColors]]) -> retval
cv.Octree.createWithDepth(maxDepth, pointCloud[, colors]) -> retval
cv.Octree_createWithDepth(maxDepth, size[, origin[, withColors]]) -> retval
cv.Octree_createWithDepth(maxDepth, pointCloud[, colors]) -> retval

Create an Octree from the PointCloud data with the specific maxDepth.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters
maxDepthMax depth of the octree
pointCloudpoint cloud data, should be 3-channel float array
colorscolor attribute of point cloud in the same 3-channel float format
Returns
resulting Octree
Here is the call graph for this function:

◆ createWithResolution() [1/2]

static Ptr< Octree > cv::Octree::createWithResolution ( double  resolution,
double  size,
const Point3f origin = { },
bool  withColors = false 
)
static
Python:
cv.Octree.createWithResolution(resolution, size[, origin[, withColors]]) -> retval
cv.Octree.createWithResolution(resolution, pointCloud[, colors]) -> retval
cv.Octree_createWithResolution(resolution, size[, origin[, withColors]]) -> retval
cv.Octree_createWithResolution(resolution, pointCloud[, colors]) -> retval

Creates an empty Octree with given resolution.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters
resolutionThe size of the octree leaf node
sizebounding box size for the Octree
originInitial center coordinate
withColorsWhether to keep per-point colors or not
Returns
resulting Octree

◆ createWithResolution() [2/2]

static Ptr< Octree > cv::Octree::createWithResolution ( double  resolution,
InputArray  pointCloud,
InputArray  colors = noArray() 
)
static
Python:
cv.Octree.createWithResolution(resolution, size[, origin[, withColors]]) -> retval
cv.Octree.createWithResolution(resolution, pointCloud[, colors]) -> retval
cv.Octree_createWithResolution(resolution, size[, origin[, withColors]]) -> retval
cv.Octree_createWithResolution(resolution, pointCloud[, colors]) -> retval

Create an Octree from the PointCloud data with the specific resolution.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters
resolutionThe size of the octree leaf node
pointCloudpoint cloud data, should be 3-channel float array
colorscolor attribute of point cloud in the same 3-channel float format
Returns
resulting octree
Here is the call graph for this function:

◆ deletePoint()

bool cv::Octree::deletePoint ( const Point3f point)
Python:
cv.Octree.deletePoint(point) -> retval

Delete a given point from the Octree.

Delete the corresponding element from the pointList in the corresponding leaf node. If the leaf node does not contain other points after deletion, this node will be deleted. In the same way, its parent node may also be deleted if its last child is deleted.

Parameters
pointThe point coordinates, comparison is epsilon-based
Returns
return ture if the point is deleted successfully.

◆ empty()

bool cv::Octree::empty ( ) const
Python:
cv.Octree.empty() -> retval

returns true if the rootnode is NULL.

◆ getPointCloudByOctree()

void cv::Octree::getPointCloudByOctree ( OutputArray  restoredPointCloud,
OutputArray  restoredColor = noArray() 
)
Python:
cv.Octree.getPointCloudByOctree([, restoredPointCloud[, restoredColor]]) -> restoredPointCloud, restoredColor

restore point cloud data from Octree.

Restore the point cloud data from existing octree. The points in same leaf node will be seen as the same point. This point is the center of the leaf node. If the resolution is small, it will work as a downSampling function.

Parameters
restoredPointCloudThe output point cloud data, can be replaced by noArray() if not needed
restoredColorThe color attribute of point cloud data, can be omitted if not needed
Here is the call graph for this function:

◆ insertPoint()

bool cv::Octree::insertPoint ( const Point3f point,
const Point3f color = { } 
)
Python:
cv.Octree.insertPoint(point[, color]) -> retval

Insert a point data with color to a OctreeNode.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Parameters
pointThe point data in Point3f format.
colorThe color attribute of point in Point3f format.
Returns
Returns whether the insertion is successful.

◆ isPointInBound()

bool cv::Octree::isPointInBound ( const Point3f point) const
Python:
cv.Octree.isPointInBound(point) -> retval

Determine whether the point is within the space range of the specific cube.

Parameters
pointThe point coordinates.
Returns
If point is in bound, return ture. Otherwise, false.

◆ KNNSearch() [1/2]

void cv::Octree::KNNSearch ( const Point3f query,
const int  K,
OutputArray  points,
OutputArray  colors,
OutputArray  squareDists 
) const
Python:
cv.Octree.KNNSearch(query, K[, points[, squareDists]]) -> points, squareDists
cv.Octree.KNNSearch(query, K[, points[, colors[, squareDists]]]) -> points, colors, squareDists

K Nearest Neighbor Search in Octree.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Find the K nearest neighbors to the query point.

Parameters
queryQuery point.
Kamount of nearest neighbors to find
pointsPoint output. Contains K points in 3-float format, arranged in order of distance from near to far, can be replaced by noArray() if not needed
colorsColor output. Contains colors corresponding to points in pointSet, can be replaced by noArray() if not needed
squareDistsDist output. Contains K squared distance in floats, arranged in order of distance from near to far, can be replaced by noArray() if not needed

◆ KNNSearch() [2/2]

void cv::Octree::KNNSearch ( const Point3f query,
const int  K,
OutputArray  points,
OutputArray  squareDists = noArray() 
) const
Python:
cv.Octree.KNNSearch(query, K[, points[, squareDists]]) -> points, squareDists
cv.Octree.KNNSearch(query, K[, points[, colors[, squareDists]]]) -> points, colors, squareDists

K Nearest Neighbor Search in Octree.

Find the K nearest neighbors to the query point.

Parameters
queryQuery point.
Kamount of nearest neighbors to find
pointsPoint output. Contains K points in 3-float format, arranged in order of distance from near to far, can be replaced by noArray() if not needed
squareDistsDist output. Contains K squared distance in floats, arranged in order of distance from near to far, can be omitted if not needed
Here is the call graph for this function:

◆ radiusNNSearch() [1/2]

int cv::Octree::radiusNNSearch ( const Point3f query,
float  radius,
OutputArray  points,
OutputArray  colors,
OutputArray  squareDists 
) const
Python:
cv.Octree.radiusNNSearch(query, radius[, points[, squareDists]]) -> retval, points, squareDists
cv.Octree.radiusNNSearch(query, radius[, points[, colors[, squareDists]]]) -> retval, points, colors, squareDists

Radius Nearest Neighbor Search in Octree.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Search all points that are less than or equal to radius. And return the number of searched points.

Parameters
queryQuery point.
radiusRetrieved radius value.
pointsPoint output. Contains searched points in 3-float format, and output vector is not in order, can be replaced by noArray() if not needed
colorsColor output. Contains colors corresponding to points in pointSet, can be replaced by noArray() if not needed
squareDistsDist output. Contains searched squared distance in floats, and output vector is not in order, can be replaced by noArray() if not needed
Returns
the number of searched points.

◆ radiusNNSearch() [2/2]

int cv::Octree::radiusNNSearch ( const Point3f query,
float  radius,
OutputArray  points,
OutputArray  squareDists = noArray() 
) const
Python:
cv.Octree.radiusNNSearch(query, radius[, points[, squareDists]]) -> retval, points, squareDists
cv.Octree.radiusNNSearch(query, radius[, points[, colors[, squareDists]]]) -> retval, points, colors, squareDists

Radius Nearest Neighbor Search in Octree.

Search all points that are less than or equal to radius. And return the number of searched points.

Parameters
queryQuery point.
radiusRetrieved radius value.
pointsPoint output. Contains searched points in 3-float format, and output vector is not in order, can be replaced by noArray() if not needed
squareDistsDist output. Contains searched squared distance in floats, and output vector is not in order, can be omitted if not needed
Returns
the number of searched points.
Here is the call graph for this function:

Member Data Documentation

◆ p

Ptr<Impl> cv::Octree::p
protected

The documentation for this class was generated from the following file: