Ocean::Geometry::NonLinearOptimizationPose Class Reference
This class implements non linear optimization algorithms for camera poses. More...
Inheritance diagram for Ocean::Geometry::NonLinearOptimizationPose:
Static Public Member Functions | |
| static bool | optimizePose (const PinholeCamera &pinholeCamera, const HomogenousMatrix4 &world_T_camera, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, const bool distortImagePoints, HomogenousMatrix4 &world_T_optimizedCamera, const unsigned int iterations=20u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=10, Scalar *initialError=nullptr, Scalar *finalError=nullptr) |
| Deprecated. More... | |
| static bool | optimizePose (const AnyCamera &anyCamera, const HomogenousMatrix4 &world_T_camera, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, HomogenousMatrix4 &world_T_optimizedCamera, const unsigned int iterations=20u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=10, Scalar *initialError=nullptr, Scalar *finalError=nullptr) |
| Minimizes the projection error of a given 6DOF pose holding orientation and translation parameters for any camera. More... | |
| static bool | optimizePose (const AnyCamera &camera, const HomogenousMatrix4 &world_T_camera, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, HomogenousMatrix4 &world_T_optimizedCamera, const unsigned int iterations, const Estimator::EstimatorType estimator, Scalar lambda, const Scalar lambdaFactor, Scalar *initialError, Scalar *finalError, const Matrix *invertedCovariances) |
| Minimizes the projection error of a given 6-DOF camera pose. More... | |
| static bool | optimizePose (const PinholeCamera &pinholeCamera, const HomogenousMatrix4 &world_T_camera, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, const bool distortImagePoints, HomogenousMatrix4 &world_T_optimizedCamera, const unsigned int iterations, const Estimator::EstimatorType estimator, Scalar lambda, const Scalar lambdaFactor, Scalar *initialError, Scalar *finalError, const Matrix *invertedCovariances) |
| Deprecated. More... | |
| static bool | optimizePoseZoom (const PinholeCamera &pinholeCamera, const HomogenousMatrix4 &world_T_camera, const Scalar zoom, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, const bool distortImagePoints, HomogenousMatrix4 &world_T_optimizedCamera, Scalar &optimizedZoom, const unsigned int iterations=20u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=10, Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr) |
| Minimizes the projection error of a given 6DOF pose holding orientation and translation parameters together with a flexible zoom. More... | |
| static bool | optimizePoseIF (const PinholeCamera &pinholeCamera, const HomogenousMatrix4 &flippedCamera_T_world, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, const bool distortImagePoints, HomogenousMatrix4 &optimizedInvertedFlippedPose, const unsigned int iterations=20u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=10, Scalar *initialError=nullptr, Scalar *finalError=nullptr) |
| Deprecated. More... | |
| static bool | optimizePoseIF (const AnyCamera &anyCamera, const HomogenousMatrix4 &flippedCamera_T_world, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, HomogenousMatrix4 &optimizedPose_flippedCamera_T_world, const unsigned int iterations=20u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=10, Scalar *initialError=nullptr, Scalar *finalError=nullptr) |
| Minimizes the projection error of a given inverted and flipped 6DOF pose holding orientation and translation parameters for any camera. More... | |
| static bool | optimizePoseIF (const AnyCamera &camera, const HomogenousMatrix4 &flippedCamera_T_world, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, HomogenousMatrix4 &optimizedFlippedCamera_T_world, const unsigned int iterations, const Estimator::EstimatorType estimator, Scalar lambda, const Scalar lambdaFactor, Scalar *initialError, Scalar *finalError, const Matrix *invertedCovariances) |
| Minimizes the projection error of a given 6-DOF camera pose. More... | |
| static bool | optimizePoseIF (const PinholeCamera &pinholeCamera, const HomogenousMatrix4 &flippedCamera_T_world, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, const bool distortImagePoints, HomogenousMatrix4 &optimizedInvertedFlippedPose, const unsigned int iterations, const Estimator::EstimatorType estimator, Scalar lambda, const Scalar lambdaFactor, Scalar *initialError, Scalar *finalError, const Matrix *invertedCovariances) |
| Deprecated. More... | |
| static bool | optimizePoseZoomIF (const PinholeCamera &pinholeCamera, const HomogenousMatrix4 &flippedCamera_T_world, const Scalar zoom, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, const bool distortImagePoints, HomogenousMatrix4 &optimizedInvertedFlippedPose, Scalar &optimizedZoom, const unsigned int iterations=20u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=10, Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr) |
| Minimizes the projection error of a given inverted and flipped 6DOF pose holding orientation and translation parameters together with a flexible zoom. More... | |
Additional Inherited Members | |
 Static Protected Member Functions inherited from Ocean::Geometry::NonLinearOptimization | |
| template<typename T > | |
| static bool | denseOptimization (T &provider, const unsigned int iterations=5u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr, Scalars *intermediateErrors=nullptr) |
| Invokes the optimization of a dense (matrix) optimization problem. More... | |
| template<typename T , Estimator::EstimatorType tEstimator> | |
| static bool | denseOptimization (T &provider, const unsigned int iterations=5u, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr, Scalars *intermediateErrors=nullptr) |
| Invokes the optimization of a dense (matrix) optimization problem. More... | |
| template<typename T > | |
| static bool | sparseOptimization (T &provider, const unsigned int iterations=5u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr, Scalars *intermediateErrors=nullptr) |
| Invokes the optimization of a sparse (matrix) optimization problem. More... | |
| template<typename T , Estimator::EstimatorType tEstimator> | |
| static bool | sparseOptimization (T &provider, const unsigned int iterations=5u, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr, Scalars *intermediateErrors=nullptr) |
| Invokes the optimization of a sparse (matrix) optimization problem. More... | |
| template<typename T > | |
| static bool | advancedDenseOptimization (T &advancedDenseProvider, const unsigned int iterations, Scalar lambda, const Scalar lambdaFactor, Scalar *initialError=nullptr, Scalar *finalError=nullptr, Scalars *intermediateErrors=nullptr) |
| Invokes the optimization of a dense (matrix) optimization problem using an advanced optimization provider. More... | |
| template<typename T > | |
| static bool | advancedSparseOptimization (T &advancedSparseProvider, const unsigned int iterations, Scalar lambda, const Scalar lambdaFactor, Scalar *initialError=nullptr, Scalar *finalError=nullptr, Scalars *intermediateErrors=nullptr) |
| Invokes the optimization of a sparse (matrix) optimization problem using an advanced optimization provider. More... | |
| template<Estimator::EstimatorType tEstimator> | |
| static Scalar | sqrErrors2robustErrors2 (const Scalars &sqrErrors, const size_t modelParameters, Vector2 *weightedErrors, Vector2 *weightVectors, const SquareMatrix2 *transposedInvertedCovariances) |
| Translates the n/2 squared errors that correspond to n elements in the error vector to robust errors. More... | |
| template<Estimator::EstimatorType tEstimator, size_t tDimension> | |
| static Scalar | sqrErrors2robustErrors (const Scalars &sqrErrors, const size_t modelParameters, StaticBuffer< Scalar, tDimension > *weightedErrors, StaticBuffer< Scalar, tDimension > *weightVectors, const Matrix *transposedInvertedCovariances) |
| Translates the n/i squared errors that correspond to n elements in the error vector to robust errors. More... | |
| template<Estimator::EstimatorType tEstimator> | |
| static Scalar | sqrErrors2robustErrors_i (const Scalars &sqrErrors, const size_t modelParameters, const size_t dimension, Scalar *weightedErrors_i, Scalar *weightVectors_i, const Matrix *transposedInvertedCovariances_i) |
| Translates the n/i squared errors that correspond to n elements in the error vector to robust errors. More... | |
| static Scalar | sqrErrors2robustErrors2 (const Estimator::EstimatorType estimator, const Scalars &sqrErrors, const size_t modelParameters, Vector2 *weightedErrors, Vector2 *weightVectors, const SquareMatrix2 *transposedInvertedCovariances) |
| Translates the n/2 squared errors that correspond to n elements in the error vector to robust errors. More... | |
| template<size_t tDimension> | |
| static Scalar | sqrErrors2robustErrors (const Estimator::EstimatorType estimator, const Scalars &sqrErrors, const size_t modelParameters, StaticBuffer< Scalar, tDimension > *weightedErrors, StaticBuffer< Scalar, tDimension > *weightVectors, const Matrix *transposedInvertedCovariances) |
| Translates the n/i squared errors that correspond to n elements in the error vector to robust errors. More... | |
| static Scalar | sqrErrors2robustErrors_i (const Estimator::EstimatorType estimator, const Scalars &sqrErrors, const size_t modelParameters, const size_t dimension, Scalar *weightedErrors_i, Scalar *weightVectors_i, const Matrix *transposedInvertedCovariances_i) |
| Translates the n/i squared errors that correspond to n elements in the error vector to robust errors. More... | |
Detailed Description
This class implements non linear optimization algorithms for camera poses.
Member Function Documentation
◆ optimizePose() [1/4]
|
inlinestatic |
Minimizes the projection error of a given 6DOF pose holding orientation and translation parameters for any camera.
The given 6DOF pose is a standard extrinsic camera matrix.
- Parameters
-
anyCamera The camera profile defining the projection, must be valid world_T_camera 6DOF pose to minimized the projection error for, must be valid objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state world_T_optimizedCamera Resulting optimized 6DOF pose iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator
- Returns
- True, if the optimization succeeded
- See also
- optimizePoseIF().
◆ optimizePose() [2/4]
|
inlinestatic |
Minimizes the projection error of a given 6-DOF camera pose.
Beware: There is another optimizePose() function with almost identical functionality/parameter layout.
However, this function here supports covariance parameters and thus creates a bigger binary footprint.
- Parameters
-
camera The camera profile defining the projection, must be valid world_T_camera The camera pose to optimized, transforming camera points to world points, with default camera pointing towards the negative z-space with y-axis upwards, must be valid objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state world_T_optimizedCamera The resulting optimized 6-DOF camera pose, transforming camera points to world points, with default camera pointing towards the negative z-space with y-axis upwards, must be valid iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator, nullptr to avoid the usage of the return value finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator, nullptr to avoid the usage of the return value invertedCovariances Optional 2x2 inverted covariance matrices which represent the uncertainties of the image points, one for each image point (a (2*n)x2 matrix)
- Returns
- True, if the optimization succeeded
- See also
- optimizePoseIF().
◆ optimizePose() [3/4]
|
inlinestatic |
Deprecated.
Minimizes the projection error of a given 6DOF pose holding orientation and translation parameters. The given 6DOF pose is a standard extrinsic camera matrix.
Beware: There is another optimizePose() function with almost identical functionality/parameter layout.
However, this function here supports covariance parameters and thus creates a bigger binary footprint.
- Parameters
-
pinholeCamera The pinhole camera object defining the projection between 3D object points and 2D image points world_T_camera 6DOF pose to minimized the projection error for, must be valid objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state distortImagePoints True, to force the usage of the distortion parameters of the given camera object to distort the projected 2D image points before error determination world_T_optimizedCamera Resulting optimized 6DOF pose iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator, nullptr to avoid the usage of the return value finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator, nullptr to avoid the usage of the return value invertedCovariances Set of 2x2 inverted covariance matrices that represent the uncertainties of the image points (a 2*n x 2 matrix)
- Returns
- True, if the optimization succeeded
- See also
- optimizePoseIF().
◆ optimizePose() [4/4]
|
inlinestatic |
Deprecated.
Minimizes the projection error of a given 6DOF pose holding orientation and translation parameters for a pinhole camera. The given 6DOF pose is a standard extrinsic camera matrix.
Beware: There is another optimizePose() function with almost identical functionality/parameter layout.
However, this function here does not support covariance parameters and thus creates a smaller binary footprint.
In case binary size matters, try to use this function only, and do not mix the usage of both options.
- Parameters
-
pinholeCamera The pinhole camera object defining the projection between 3D object points and 2D image points, must be valid world_T_camera 6DOF pose to minimized the projection error for, must be valid objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state distortImagePoints True, to force the usage of the distortion parameters of the given camera object to distort the projected 2D image points before error determination world_T_optimizedCamera Resulting optimized 6DOF pose iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator
- Returns
- True, if the optimization succeeded
- See also
- optimizePoseIF().
◆ optimizePoseIF() [1/4]
|
static |
Minimizes the projection error of a given inverted and flipped 6DOF pose holding orientation and translation parameters for any camera.
Beware: The given inverted and flipped 6DOF pose is not equivalent to a standard extrinsic camera matrix.
- Parameters
-
anyCamera The camera profile defining the projection, must be valid flippedCamera_T_world 6DOF pose to minimized the projection error for (inverted and flipped), must be valid objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state optimizedPose_flippedCamera_T_world Resulting optimized 6DOF pose (inverted and flipped) iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator
- Returns
- True, if succeeded
- See also
- optimizePose().
◆ optimizePoseIF() [2/4]
|
static |
Minimizes the projection error of a given 6-DOF camera pose.
Beware: There is another optimizePose() function with almost identical functionality/parameter layout.
However, this function here supports covariance parameters and thus creates a bigger binary footprint.
- Parameters
-
camera The camera profile defining the projection, must be valid flippedCamera_T_world The inverted and flipped camera pose to optimized, transforming world points to flipped camera points, with default camera pointing towards the positive z-space with y-axis downwards, must be valid objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state optimizedFlippedCamera_T_world The resulting optimized inverted and flipped camera pose, transforming world points to flipped camera points, with default camera pointing towards the positive z-space with y-axis downwards, must be valid iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator, nullptr to avoid the usage of the return value finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator, nullptr to avoid the usage of the return value invertedCovariances Optional 2x2 inverted covariance matrices which represent the uncertainties of the image points, one for each image point (a (2*n)x2 matrix)
- Returns
- True, if the optimization succeeded
- See also
- optimizePose().
◆ optimizePoseIF() [3/4]
|
static |
Deprecated.
Minimizes the projection error of a given inverted and flipped 6DOF pose holding orientation and translation parameters. Beware: The given inverted and flipped 6DOF pose is not equivalent to a standard extrinsic camera matrix.
Beware: There is another optimizePoseIF() function with almost identical functionality/parameter layout.
However, this function here supports covariance parameters and thus creates a bigger binary footprint.
- Parameters
-
pinholeCamera The pinhole camera object defining the projection between 3D object points and 2D image points flippedCamera_T_world 6DOF pose to minimized the projection error for (inverted and flipped), must be valid objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state distortImagePoints True, to force the usage of the distortion parameters of the given camera object to distort the projected 2D image points before error determination optimizedInvertedFlippedPose Resulting optimized 6DOF pose (inverted and flipped) iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator, nullptr to avoid the usage of the return value finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator, nullptr to avoid the usage of the return value invertedCovariances Optional set of 2x2 inverted covariance matrices that represent the uncertainties of the image points (a 2*n x 2 matrix)
- Returns
- True, if succeeded
- See also
- optimizePose().
◆ optimizePoseIF() [4/4]
|
static |
Deprecated.
Minimizes the projection error of a given inverted and flipped 6DOF pose holding orientation and translation parameters for a pinhole camera. Beware: The given inverted and flipped 6DOF pose is not equivalent to a standard extrinsic camera matrix.
Beware: There is another optimizePoseIF() function with almost identical functionality/parameter layout.
However, this function here does not support covariance parameters and thus creates a smaller binary footprint.
In case binary size matters, try to use this function only, and do not mix the usage of both options.
- Parameters
-
pinholeCamera The pinhole camera object defining the projection between 3D object points and 2D image points flippedCamera_T_world 6DOF pose to minimized the projection error for (inverted and flipped), must be valid objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state distortImagePoints True, to force the usage of the distortion parameters of the given camera object to distort the projected 2D image points before error determination optimizedInvertedFlippedPose Resulting optimized 6DOF pose (inverted and flipped) iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator
- Returns
- True, if succeeded
- See also
- optimizePose().
◆ optimizePoseZoom()
|
inlinestatic |
Minimizes the projection error of a given 6DOF pose holding orientation and translation parameters together with a flexible zoom.
The given 6DOF pose is a standard extrinsic camera matrix.
- Parameters
-
pinholeCamera The pinhole camera object defining the projection between 3D object points and 2D image points world_T_camera 6DOF pose to minimized the projection error for, must be valid zoom The scalar zoom factor matching to the given pose, with range (0, infinity) objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state distortImagePoints True, to force the usage of the distortion parameters of the given camera object to distort the projected 2D image points before error determination world_T_optimizedCamera Resulting optimized 6DOF pose optimizedZoom Resulting optimized zoom factor matching to the resulting optimized pose, with range (0, infinity) iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator invertedCovariances Optional set of 2x2 inverted covariance matrices that represent the uncertainties of the image points (a 2*n x 2 matrix)
- Returns
- True, if the optimization succeeded
- See also
- optimizePoseIF().
◆ optimizePoseZoomIF()
|
static |
Minimizes the projection error of a given inverted and flipped 6DOF pose holding orientation and translation parameters together with a flexible zoom.
Beware: The given inverted and flipped 6DOF pose is not equivalent to a standard extrinsic camera matrix.
- Parameters
-
pinholeCamera The pinhole camera object defining the projection between 3D object points and 2D image points flippedCamera_T_world 6DOF pose to minimized the projection error for (inverted and flipped), must be valid zoom The scalar zoom factor matching to the given pose, with range (0, infinity) objectPoints 3D object points to be projected into the camera plane imagePoints 2D image points corresponding to the object points, the image points may be distorted or undistorted depending on the usage of the distortImagePoints state distortImagePoints True, to force the usage of the distortion parameters of the given camera object to distort the projected 2D image points before error determination optimizedInvertedFlippedPose Resulting optimized 6DOF pose (inverted and flipped) optimizedZoom Resulting optimized zoom factor matching to the resulting optimized pose, with range (0, infinity) iterations Number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator Robust error estimator to be used lambda Initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged pixel error for the given initial parameters, in relation to the defined estimator finalError Optional resulting averaged pixel error for the final optimized parameters, in relation to the defined estimator invertedCovariances Optional set of 2x2 inverted covariance matrices that represent the uncertainties of the image points (a 2*n x 2 matrix)
- Returns
- True, if succeeded
- See also
- optimizePose().
The documentation for this class was generated from the following file:
