OpenCV 5.0.0-pre
Open Source Computer Vision
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cv::Odometry Class Reference

#include <opencv2/3d/odometry.hpp>

Collaboration diagram for cv::Odometry:

Public Member Functions

 Odometry ()
 
 Odometry (OdometryType otype)
 
 Odometry (OdometryType otype, const OdometrySettings &settings, OdometryAlgoType algtype)
 
 ~Odometry ()
 
bool compute (const OdometryFrame &srcFrame, const OdometryFrame &dstFrame, OutputArray Rt) const
 
bool compute (InputArray srcDepth, InputArray dstDepth, OutputArray Rt) const
 Compute Rigid Transformation between two frames so that Rt * src = dst.
 
bool compute (InputArray srcDepth, InputArray srcRGB, InputArray dstDepth, InputArray dstRGB, OutputArray Rt) const
 Compute Rigid Transformation between two frames so that Rt * src = dst.
 
Ptr< RgbdNormalsgetNormalsComputer () const
 Get the normals computer object used for normals calculation (if presented). The normals computer is generated at first need during prepareFrame when normals are required for the ICP algorithm but not presented by a user. Re-generated each time the related settings change or a new frame arrives with the different size.
 
void prepareFrame (OdometryFrame &frame) const
 
void prepareFrames (OdometryFrame &srcFrame, OdometryFrame &dstFrame) const
 

Constructor & Destructor Documentation

◆ Odometry() [1/3]

cv::Odometry::Odometry ( )
Python:
cv.Odometry() -> <Odometry object>
cv.Odometry(otype) -> <Odometry object>
cv.Odometry(otype, settings, algtype) -> <Odometry object>

◆ Odometry() [2/3]

cv::Odometry::Odometry ( OdometryType otype)
explicit
Python:
cv.Odometry() -> <Odometry object>
cv.Odometry(otype) -> <Odometry object>
cv.Odometry(otype, settings, algtype) -> <Odometry object>

◆ Odometry() [3/3]

cv::Odometry::Odometry ( OdometryType otype,
const OdometrySettings & settings,
OdometryAlgoType algtype )
Python:
cv.Odometry() -> <Odometry object>
cv.Odometry(otype) -> <Odometry object>
cv.Odometry(otype, settings, algtype) -> <Odometry object>

◆ ~Odometry()

cv::Odometry::~Odometry ( )

Member Function Documentation

◆ compute() [1/3]

bool cv::Odometry::compute ( const OdometryFrame & srcFrame,
const OdometryFrame & dstFrame,
OutputArray Rt ) const
Python:
cv.Odometry.compute(srcFrame, dstFrame[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, dstDepth[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, srcRGB, dstDepth, dstRGB[, Rt]) -> retval, Rt

Compute Rigid Transformation between two frames so that Rt * src = dst Both frames, source and destination, should have been prepared by calling prepareFrame() first

Parameters
srcFramesrc frame ("original" image)
dstFramedst frame ("rotated" image)
RtRigid transformation, which will be calculated, in form: { R_11 R_12 R_13 t_1 R_21 R_22 R_23 t_2 R_31 R_32 R_33 t_3 0 0 0 1 }
Returns
true on success, false if failed to find the transformation

◆ compute() [2/3]

bool cv::Odometry::compute ( InputArray srcDepth,
InputArray dstDepth,
OutputArray Rt ) const
Python:
cv.Odometry.compute(srcFrame, dstFrame[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, dstDepth[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, srcRGB, dstDepth, dstRGB[, Rt]) -> retval, Rt

Compute Rigid Transformation between two frames so that Rt * src = dst.

Parameters
srcDepthsource depth ("original" image)
dstDepthdestination depth ("rotated" image)
RtRigid transformation, which will be calculated, in form: { R_11 R_12 R_13 t_1 R_21 R_22 R_23 t_2 R_31 R_32 R_33 t_3 0 0 0 1 }
Returns
true on success, false if failed to find the transformation

◆ compute() [3/3]

bool cv::Odometry::compute ( InputArray srcDepth,
InputArray srcRGB,
InputArray dstDepth,
InputArray dstRGB,
OutputArray Rt ) const
Python:
cv.Odometry.compute(srcFrame, dstFrame[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, dstDepth[, Rt]) -> retval, Rt
cv.Odometry.compute(srcDepth, srcRGB, dstDepth, dstRGB[, Rt]) -> retval, Rt

Compute Rigid Transformation between two frames so that Rt * src = dst.

Parameters
srcDepthsource depth ("original" image)
srcRGBsource RGB
dstDepthdestination depth ("rotated" image)
dstRGBdestination RGB
RtRigid transformation, which will be calculated, in form: { R_11 R_12 R_13 t_1 R_21 R_22 R_23 t_2 R_31 R_32 R_33 t_3 0 0 0 1 }
Returns
true on success, false if failed to find the transformation

◆ getNormalsComputer()

Ptr< RgbdNormals > cv::Odometry::getNormalsComputer ( ) const
Python:
cv.Odometry.getNormalsComputer() -> retval

Get the normals computer object used for normals calculation (if presented). The normals computer is generated at first need during prepareFrame when normals are required for the ICP algorithm but not presented by a user. Re-generated each time the related settings change or a new frame arrives with the different size.

◆ prepareFrame()

void cv::Odometry::prepareFrame ( OdometryFrame & frame) const
Python:
cv.Odometry.prepareFrame(frame) -> None

Prepare frame for odometry calculation

Parameters
frameodometry prepare this frame as src frame and dst frame simultaneously

◆ prepareFrames()

void cv::Odometry::prepareFrames ( OdometryFrame & srcFrame,
OdometryFrame & dstFrame ) const
Python:
cv.Odometry.prepareFrames(srcFrame, dstFrame) -> None

Prepare frame for odometry calculation

Parameters
srcFrameframe will be prepared as src frame ("original" image)
dstFrameframe will be prepared as dsr frame ("rotated" image)

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