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Ocean::Geometry::NonLinearOptimizationOrientation Class Reference
This class implements least square or robust optimization algorithms for orientations. More...
#include <NonLinearOptimizationOrientation.h>
Inheritance diagram for Ocean::Geometry::NonLinearOptimizationOrientation:
Static Public Member Functions | |
| static bool | optimizeOrientation (const AnyCamera &camera, const Quaternion &world_R_camera, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, Quaternion &world_R_optimizedCamera, const unsigned int iterations, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, const Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr, Scalars *intermediateErrors=nullptr) |
| Minimizes the projection error of a given (pure rotational) 3-DOF camera pose. | |
| static bool | optimizeOrientationIF (const AnyCamera &camera, const Quaternion &flippedCamera_R_world, const ConstIndexedAccessor< Vector3 > &objectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, Quaternion &optimizedFlippedCamera_R_world, const unsigned int iterations, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, const Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr, Scalars *intermediateErrors=nullptr) |
| Minimizes the projection error of a given (pure rotational) 3-DOF camera pose. | |
| static bool | optimizeCameraOrientation (const PinholeCamera &pinholeCamera, const SquareMatrix3 &world_R_camera, const ConstIndexedAccessor< ObjectPoint > &objectPoints, const ConstIndexedAccessor< ImagePoint > &imagePoints, const bool distortImagePoints, SquareMatrix3 &world_R_optimizedCamera, PinholeCamera &optimizedCamera, const unsigned int iterations, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, const Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr, Scalars *intermediateErrors=nullptr) |
| Minimizes the projection error of a given 3DOF orientation and the entire camera parameters (intrinsic and distortion). | |
| static bool | optimizeCameraOrientationIF (const PinholeCamera &pinholeCamera, const SquareMatrix3 &flippedCamera_R_world, const ConstIndexedAccessor< ObjectPoint > &objectPoints, const ConstIndexedAccessor< ImagePoint > &imagePoints, const bool distortImagePoints, SquareMatrix3 &optimizedFlippedCamera_R_world, PinholeCamera &optimizedCamera, const unsigned int iterations, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, const Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr, const Matrix *invertedCovariances=nullptr, Scalars *intermediateErrors=nullptr) |
| Minimizes the projection error of a given inverted and flipped 3DOF orientation and the entire camera parameters (intrinsic and distortion). | |
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. | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
| 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. | |
Detailed Description
This class implements least square or robust optimization algorithms for orientations.
Member Function Documentation
◆ optimizeCameraOrientation()
|
inlinestatic |
Minimizes the projection error of a given 3DOF orientation and the entire camera parameters (intrinsic and distortion).
The given 3DOF orientation is the rotational part of a standard extrinsic camera matrix.
- Parameters
-
pinholeCamera The pinhole camera object defining the projection between 3D object points and 2D image points world_R_camera 3DOF orientation to minimize the projection error for objectPoints The accessor providing the 3D object points to be projected into the camera plane imagePoints The accessor providing the 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_R_optimizedCamera Resulting optimized 3DOF orientation optimizedCamera The resulting optimized camera with modified intrinsic camera parameters and distortion parameters iterations Number of iterations to be applied at most, if no convergence can be reached 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 robust pixel error for the given initial parameters depending on the selected estimator finalError Optional resulting averaged robust pixel error for the final optimized parameters depending on the selected estimator invertedCovariances Optional set of 2x2 inverted covariance matrices that represent the uncertainties of the image points (a 2*n x 2 matrix) intermediateErrors Optional resulting intermediate (improving) errors
- Returns
- True, if the optimization succeeded
- See also
- optimizeOrientationIF().
◆ optimizeCameraOrientationIF()
|
static |
Minimizes the projection error of a given inverted and flipped 3DOF orientation and the entire camera parameters (intrinsic and distortion).
Beware: The given inverted and flipped 3DOF orientation is not equivalent to the rotational part of a standard extrinsic camera matrix.
- Parameters
-
pinholeCamera The pinhole camera object defining the projection between 3D object points and 2D image points flippedCamera_R_world 3DOF orientation to minimize the projection error for (inverted and flipped) objectPoints The accessor providing the 3D object points to be projected into the camera plane imagePoints The accessor providing the 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 optimizedFlippedCamera_R_world Resulting optimized 3DOF orientation (inverted and flipped) optimizedCamera The resulting optimized camera with modified intrinsic camera parameters and distortion parameters iterations Number of iterations to be applied at most, if no convergence can be reached 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 robust pixel error for the given initial parameters depending on the selected estimator finalError Optional resulting averaged robust pixel error for the final optimized parameters depending on the selected estimator invertedCovariances Optional set of 2x2 inverted covariance matrices that represent the uncertainties of the image points (a 2*n x 2 matrix) intermediateErrors Optional resulting intermediate (improving) errors
- Returns
- True, if the optimization succeeded
- See also
- optimizeOrientationIF().
◆ optimizeOrientation()
|
inlinestatic |
Minimizes the projection error of a given (pure rotational) 3-DOF camera pose.
- Parameters
-
camera The camera profile defining the projection between 3D object points and 2D image points, must be valid world_R_camera The 3-DOF camera pose to optimize, with default camera pointing towards the negative z-space, with y-axis upwards, must be valid objectPoints The accessor providing the 3D object points to be projected into the camera plane imagePoints The accessor providing the 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_R_optimizedCamera The resulting optimized 3-DOF camera pose, with default camera pointing towards the negative z-space, with y-axis upwards iterations The number of iterations to be applied at most, if no convergence can be reached, with range [1, infinity) estimator The robust error estimator to be used lambda The initial Levenberg-Marquardt damping value which may be changed after each iteration using the damping factor, with range [0, infinity) lambdaFactor The Levenberg-Marquardt damping factor to be applied to the damping value, with range [1, infinity) initialError Optional resulting averaged robust pixel error for the given initial parameters depending on the selected estimator finalError Optional resulting averaged robust pixel error for the final optimized parameters depending on the selected estimator invertedCovariances Optional set of 2x2 inverted covariance matrices that represent the uncertainties of the image points (a 2*n x 2 matrix) intermediateErrors Optional resulting intermediate (improving) errors
- Returns
- True, if the optimization succeeded
- See also
- optimizeOrientationIF().
◆ optimizeOrientationIF()
|
static |
Minimizes the projection error of a given (pure rotational) 3-DOF camera pose.
- Parameters
-
camera The camera profile defining the projection between 3D object points and 2D image points, must be valid flippedCamera_R_world The inverted and flipped 3-DOF camera pose to optimize, with flipped camera pointing towards the positive z-space, with y-axis downwards, must be valid objectPoints The accessor providing the 3D object points to be projected into the camera plane imagePoints The accessor providing the 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 optimizedFlippedCamera_R_world The resulting optimized flipped and inverted 3-DOF camera pose, with flipped camera pointing towards the positive z-space, with y-axis downwards iterations Number of iterations to be applied at most, if no convergence can be reached 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 robust pixel error for the given initial parameters depending on the selected estimator finalError Optional resulting averaged robust pixel error for the final optimized parameters depending on the selected estimator invertedCovariances Optional set of 2x2 inverted covariance matrices that represent the uncertainties of the image points (a 2*n x 2 matrix) intermediateErrors Optional resulting intermediate (improving) errors
- Returns
- True, if succeeded
- See also
- optimizeOrientation().
The documentation for this class was generated from the following file:
