Ocean::Geometry::NonLinearOptimizationCamera Class Reference
This class implements least square or robust optimization algorithms for camera profiles. More...
Inheritance diagram for Ocean::Geometry::NonLinearOptimizationCamera:
Data Structures | |
| class | CameraObjectPointsPosesData |
| Forward declaration of the data class allowing to optimized the camera parameters for unconstrained (translational and rotational) camera motion. More... | |
| class | CameraOrientationsData |
| Forward declaration of the data class allowing to optimized the camera parameters for rotational camera motion. More... | |
| class | CameraProfileBaseData |
| Forward declaration of a base class allowing to optimized the camera profile. More... | |
| class | CameraProvider |
| Forward declaration of an optimization provider allowing to optimize the individual parameters of a camera profile. More... | |
Static Public Member Functions | |
| static bool | findInitialFieldOfView (const PinholeCamera &pinholeCamera, const ConstIndexedAccessor< SquareMatrix3 > &orientations, const PoseGroupsAccessor &correspondenceGroups, PinholeCamera &optimizedCamera, NonconstIndexedAccessor< SquareMatrix3 > *optimizedOrientations, const Scalar lowerFovX=Numeric::deg2rad(40), const Scalar upperFovX=Numeric::deg2rad(90), const unsigned int steps=10u, const unsigned int recursiveIterations=3u, const bool onlyFrontObjectPoints=true, bool *significantResult=nullptr, Scalar *finalError=nullptr, Worker *worker=nullptr, bool *abort=nullptr) |
| Determines the initial field of view for a set of camera frames with known orientations and groups of correspondences of ids of 3D object points and 2D image point locations from the individual frames. More... | |
| static bool | findInitialFieldOfView (const PinholeCamera &pinholeCamera, const ConstIndexedAccessor< HomogenousMatrix4 > &poses, const ConstIndexedAccessor< Vector3 > &objectPoints, const ObjectPointGroupsAccessor &correspondenceGroups, PinholeCamera &optimizedCamera, NonconstIndexedAccessor< HomogenousMatrix4 > *optimizedPoses, NonconstIndexedAccessor< Vector3 > *optimizedObjectPoints, const Scalar lowerFovX=Numeric::deg2rad(40), const Scalar upperFovX=Numeric::deg2rad(90), const unsigned int steps=10u, const unsigned int recursiveIterations=3u, const bool onlyFrontObjectPoints=true, bool *significantResult=nullptr, Scalar *finalError=nullptr, Worker *worker=nullptr, bool *abort=nullptr) |
| Determines the initial field of view for a set of camera frames with known poses and groups of correspondences between pose indices and 2D image points locations within the pose frames while also the provided object points are optimized. More... | |
| static bool | optimizeCamera (const PinholeCamera &pinholeCamera, const ConstIndexedAccessor< Vector2 > &normalizedObjectPoints, const ConstIndexedAccessor< Vector2 > &imagePoints, const PinholeCamera::OptimizationStrategy optimizationStrategy, PinholeCamera &optimizedCamera, const unsigned int iterations=20u, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), Scalar *initialError=nullptr, Scalar *finalError=nullptr) |
| Optimizes the individual parameters of a camera profile by minimizing the pixel error between normalized image points (projected 3D object points) and their corresponding 2D image point observations. More... | |
| static bool | optimizeCameraOrientations (const PinholeCamera &pinholeCamera, const ConstIndexedAccessor< SquareMatrix3 > &orientations, const PoseGroupsAccessor &correspondenceGroups, const PinholeCamera::OptimizationStrategy optimizationStrategy, PinholeCamera &optimizedCamera, NonconstIndexedAccessor< SquareMatrix3 > *optimizedOrientations, const unsigned int iterations, const Geometry::Estimator::EstimatorType estimator=Geometry::Estimator::ET_SQUARE, const Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), const bool onlyFrontObjectPoints=true, Scalar *initialError=nullptr, Scalar *finalError=nullptr, Scalars *intermediateErrors=nullptr) |
| Optimizes the camera parameters of a given camera profile for a set of camera frames with known orientation and groups of 2D/3D point correspondences from individual frames. More... | |
| static bool | optimizeCameraPoses (const PinholeCamera &pinholeCamera, const ConstIndexedAccessor< HomogenousMatrix4 > &poses, const ConstIndexedAccessor< Vectors3 > &objectPointGroups, const ConstIndexedAccessor< Vectors2 > &imagePointGroups, PinholeCamera &optimizedCamera, NonconstIndexedAccessor< HomogenousMatrix4 > *optimizedPoses, const unsigned int iterations, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), const bool onlyFrontObjectPoints=true, Scalar *initialError=nullptr, Scalar *finalError=nullptr, Scalars *intermediateErrors=nullptr) |
| Minimizes the projection error between the projections of static 3D object points and their corresponding image points in several 6DOF camera poses. More... | |
| static bool | optimizeCameraPosesIF (const PinholeCamera &pinholeCamera, const ConstIndexedAccessor< HomogenousMatrix4 > &posesIF, const ConstIndexedAccessor< Vectors3 > &objectPointGroups, const ConstIndexedAccessor< Vectors2 > &imagePointGroups, PinholeCamera &optimizedCamera, NonconstIndexedAccessor< HomogenousMatrix4 > *optimizedPosesIF, const unsigned int iterations, const Estimator::EstimatorType estimator=Estimator::ET_SQUARE, Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), const bool onlyFrontObjectPoints=true, Scalar *initialError=nullptr, Scalar *finalError=nullptr, Scalars *intermediateErrors=nullptr) |
| Minimizes the projection error between the projections of static 3D object points and their corresponding image points in several 6DOF camera poses. More... | |
| static bool | optimizeCameraObjectPointsPoses (const PinholeCamera &pinholeCamera, const ConstIndexedAccessor< HomogenousMatrix4 > &poses, const ConstIndexedAccessor< Vector3 > &objectPoints, const ObjectPointGroupsAccessor &correspondenceGroups, const PinholeCamera::OptimizationStrategy optimizationStrategy, PinholeCamera &optimizedCamera, NonconstIndexedAccessor< HomogenousMatrix4 > *optimizedPoses, NonconstIndexedAccessor< Vector3 > *optimizedObjectPoints, const unsigned int iterations, const Geometry::Estimator::EstimatorType estimator=Geometry::Estimator::ET_SQUARE, const Scalar lambda=Scalar(0.001), const Scalar lambdaFactor=Scalar(5), const bool onlyFrontObjectPoints=true, Scalar *initialError=nullptr, Scalar *finalError=nullptr, Scalars *intermediateErrors=nullptr) |
| Optimizes the camera parameters of a given camera profile for a set of given camera poses and a set of given 3D object points by minimizing the projection error between the 3D object points and the corresponding 2D image points. More... | |
Static Protected Member Functions | |
| static void | findInitialFieldOfViewSubset (const PinholeCamera *pinholeCamera, const ConstIndexedAccessor< SquareMatrix3 > *orientations, const PoseGroupsAccessor *correspondenceGroups, PinholeCamera *optimizedCamera, SquareMatrices3 *optimizedOrientations, const Scalar lowerFovX, const Scalar upperFovX, const unsigned int overallSteps, const bool onlyFrontObjectPoints, Scalar *bestError, Scalars *allErrors, Lock *lock, bool *abort, const unsigned int firstStep, const unsigned int steps) |
| Determines the initial field of view for a set of camera frames with known orientations and groups of correspondences of ids of 3D object points and 2D image point locations from the individual frames. More... | |
| static void | findInitialFieldOfViewSubset (const PinholeCamera *pinholeCamera, const ConstIndexedAccessor< HomogenousMatrix4 > *poses, const ConstIndexedAccessor< Vector3 > *objectPoints, const ObjectPointGroupsAccessor *correspondenceGroups, PinholeCamera *optimizedCamera, HomogenousMatrices4 *optimizedPoses, Vectors3 *optimizedObjectPoints, const Scalar lowerFovX, const Scalar upperFovX, const unsigned int overallSteps, const bool onlyFrontObjectPoints, Scalar *bestError, Scalars *allErrors, Lock *lock, bool *abort, const unsigned int firstStep, const unsigned int steps) |
| Determines the initial field of view for a set of camera frames with known poses and groups of correspondences between pose indices and 2D image points locations within the pose frames. More... | |
 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 least square or robust optimization algorithms for camera profiles.
Member Function Documentation
◆ findInitialFieldOfView() [1/2]
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static |
Determines the initial field of view for a set of camera frames with known poses and groups of correspondences between pose indices and 2D image points locations within the pose frames while also the provided object points are optimized.
The number of correspondences may vary between the individual frames (groups).
Each group may address individual object points, however the larger the intersection of sets between the individual 3D object points in the individual frames the better the optimization result.
- Parameters
-
pinholeCamera The pinhole camera profile for which the better field of view will be determined, must be valid poses The accessor for the known poses of the individual camera frames objectPoints The accessor for the individual 3D object points correspondenceGroups The accessor for the individual groups of correspondences between pose ids and image point location, one group for each object point optimizedCamera The resulting camera profile with best matching field of view optimizedPoses Optional accessor for the resulting optimized camera poses matching with the new camera profile optimizedObjectPoints Optional accessor for the resulting optimized object point locations lowerFovX The lower bound of the possible horizontal field of view in radian, with range (0, upperFovX] upperFovX The upper bound of the possible horizontal field of view in radian, with range [lowerFovX, PI) steps The number of steps in which the defined angle range is subdivided, with range [4, infinity) recursiveIterations The number of recursive iterations that will be applied to improve the accuracy, start with the second iteration the search for the best fov is centered at the position of the previous iteration, with range [1, infinity) onlyFrontObjectPoints True, to avoid that the optimized 3D position lies behind any camera significantResult Optional resulting whether the resulting field of view has an significant impact on the error; True, of so finalError Optional resulting averaged square pixel error for the camera profile with the best matching field of view worker Optional worker object to distribute the computation abort Optional abort statement allowing to stop the execution; True, if the execution has to stop
- Returns
- True, if succeeded and the execution has not been aborted
◆ findInitialFieldOfView() [2/2]
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static |
Determines the initial field of view for a set of camera frames with known orientations and groups of correspondences of ids of 3D object points and 2D image point locations from the individual frames.
The number of correspondences may vary between the individual frames (groups).
Each group may address individual object points, however the larger the intersection of sets between the individual 3D object points in the individual frames the better the optimization result.
- Parameters
-
pinholeCamera The pinhole camera profile for which the better field of view will be determined, must be valid orientations The accessor for the known orientations of the individual camera frames correspondenceGroups The accessor for the individual groups of point correspondences, one group for each orientation optimizedCamera The resulting camera profile with best matching field of view optimizedOrientations Optional accessor for the optimized camera orientations matching with the new camera profile lowerFovX The lower bound of the possible horizontal field of view in radian, with range (0, upperFovX] upperFovX The upper bound of the possible horizontal field of view in radian, with range [lowerFovX, PI) steps The number of steps in which the defined angle range is subdivided, with range [4, infinity) recursiveIterations The number of recursive iterations that will be applied to improve the accuracy, start with the second iteration the search for the best fov is centered at the position of the previous iteration, with range [1, infinity) onlyFrontObjectPoints True, to avoid that the optimized 3D position lies behind any camera significantResult Optional resulting whether the resulting field of view has an significant impact on the error; True, of so finalError Optional resulting averaged square pixel error for the camera profile with the best matching field of view worker Optional worker object to distribute the computation abort Optional abort statement allowing to stop the execution; True, if the execution has to stop
- Returns
- True, if succeeded and the execution has not been aborted
◆ findInitialFieldOfViewSubset() [1/2]
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staticprotected |
Determines the initial field of view for a set of camera frames with known poses and groups of correspondences between pose indices and 2D image points locations within the pose frames.
The number of correspondences may vary between the individual frames (groups).
Each group may address individual object points, however the larger the intersection of sets between the individual 3D object points in the individual frames the better the optimization result.
- Parameters
-
pinholeCamera The pinhole camera profile for which the better field of view will be determined, must be valid poses The accessor for the known poses of the individual camera frames objectPoints The accessor for the individual 3D object points correspondenceGroups The accessor for the individual groups of correspondences between pose ids and image point location, one group for each object point optimizedCamera The resulting camera profile with best matching field of view optimizedPoses Optional accessor for the resulting optimized camera poses matching with the new camera profile optimizedObjectPoints Optional accessor for the resulting optimized object point locations lowerFovX The lower bound of the possible horizontal field of view in radian, with range (0, upperFovX] upperFovX The upper bound of the possible horizontal field of view in radian, with range [lowerFovX, PI) overallSteps The overall number of steps in which the defined angle range is subdivided, with range [4, infinity) onlyFrontObjectPoints True, to avoid that the optimized 3D position lies behind any camera bestError Resulting averaged square pixel error for the camera profile with the best matching field of view allErrors Optional vector of all errors that have been determined (can be used to decide whether a resulting best camera profile is significantly different from all other camera profiles) lock Lock object, must be defined if this function is executed in parallel on individual threads, nullptr otherwise abort Optional abort statement allowing to stop the execution; True, if the execution has to stop firstStep The first step to be handled, with range [0, overallSteps) steps The number of steps which will be handled (from the entire number of overall steps), with range [1, overallSteps]
◆ findInitialFieldOfViewSubset() [2/2]
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staticprotected |
Determines the initial field of view for a set of camera frames with known orientations and groups of correspondences of ids of 3D object points and 2D image point locations from the individual frames.
The number of correspondences may vary between the individual frames (groups).
Each group may address individual object points, however the larger the intersection of sets between the individual 3D object points in the individual frames the better the optimization result.
- Parameters
-
pinholeCamera The pinhole camera profile for which the better field of view will be determined, must be valid orientations The accessor for the known orientations of the individual camera frames correspondenceGroups The accessor for the individual groups of point correspondences, one group for each orientation optimizedCamera The resulting camera profile with best matching field of view optimizedOrientations Optional accessor for the optimized camera orientations matching with the new camera profile lowerFovX The lower bound of the possible horizontal field of view in radian, with range (0, upperFovX] upperFovX The upper bound of the possible horizontal field of view in radian, with range [lowerFovX, PI) overallSteps The overall number of steps in which the defined angle range is subdivided, with range [4, infinity) onlyFrontObjectPoints True, to avoid that the optimized 3D position lies behind any camera bestError Resulting averaged square pixel error for the camera profile with the best matching field of view allErrors Optional vector of all errors that have been determined (can be used to decide whether a resulting best camera profile is significantly different from all other camera profiles) lock Lock object, must be defined if this function is executed in parallel on individual threads, nullptr otherwise abort Optional abort statement allowing to stop the execution; True, if the execution has to stop firstStep The first step to be handled, with range [0, overallSteps) steps The number of steps which will be handled (from the entire number of overall steps), with range [1, overallSteps]
◆ optimizeCamera()
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static |
Optimizes the individual parameters of a camera profile by minimizing the pixel error between normalized image points (projected 3D object points) and their corresponding 2D image point observations.
Which parameter of the camera profile will be optimized depends on the specified optimization strategy.
- Parameters
-
pinholeCamera The pinhole camera profile with initial distortion parameters to optimize normalizedObjectPoints The accessor for the projected 3D object points (the normalized image/object points) imagePoints imagePoints The accessor for the observations of the projected 3D object points, defined in the pixel coordinate system, each point corresponds to one normalized object point optimizationStrategy The optimization strategy to be used optimizedCamera Resulting optimized camera object holding optimized intrinsic 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 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
◆ optimizeCameraObjectPointsPoses()
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static |
Optimizes the camera parameters of a given camera profile for a set of given camera poses and a set of given 3D object points by minimizing the projection error between the 3D object points and the corresponding 2D image points.
This function also optimized the camera poses and the locations of the 3D object point while the camera profile is optimized.
The number of 2D/3D point correspondences may vary between the individual frames (groups).
Each group may address individual object points, however the larger the intersection of sets between the individual 3D object points in the individual frames the better the optimization result.
- Parameters
-
pinholeCamera The pinhole camera profile to optimized poses The accessor for the known poses of the individual camera frames objectPoints The accessor for the known 3D object points locations correspondenceGroups The accessor for the individual groups of correspondences between pose indices and image points, one group for each object point optimizationStrategy The optimization strategy for the camera profile optimizedCamera The resulting optimized camera profile optimizedPoses Optional accessor for the resulting optimized camera poses, matching with the new camera profile optimizedObjectPoints Optional accessor for the resulting optimized 3D object point locations, matching with the new camera profile 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) onlyFrontObjectPoints True, to avoid that the optimized 3D position lies behind any camera 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 intermediateErrors Optional resulting intermediate averaged pixel errors for the individual optimization steps, in relation to the defined estimator
- Returns
- True, if succeeded
◆ optimizeCameraOrientations()
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static |
Optimizes the camera parameters of a given camera profile for a set of camera frames with known orientation and groups of 2D/3D point correspondences from individual frames.
The number of points correspondences may vary between the individual frames (groups).
Each group may address individual object points.
- Parameters
-
pinholeCamera The pinhole camera profile to optimized orientations The accessor for the known orientations of the individual camera frames correspondenceGroups The accessor for the individual groups of point correspondences, one group for each orientation optimizationStrategy The optimization strategy optimizedCamera The resulting camera profile with ideal field of view optimizedOrientations Optional accessor for the optimized camera orientations matching with the new camera profile 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) onlyFrontObjectPoints True, to avoid that the optimized 3D position lies behind any camera 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 intermediateErrors Optional resulting intermediate averaged pixel errors for the individual optimization steps, in relation to the defined estimator
- Returns
- True, if succeeded
◆ optimizeCameraPoses()
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static |
Minimizes the projection error between the projections of static 3D object points and their corresponding image points in several 6DOF camera poses.
The camera profile as well as the camera poses are optimized concurrently. The given poses are equivalent to extrinsic camera matrices and thus define a transformation from the camera coordinate system into the world coordinate system.
- Parameters
-
pinholeCamera The pinhole camera holding intrinsic and distortion parameters to minimize the projection error for poses The individual camera poses, one pose for each pair of groups of object points and image points objectPointGroups The accessor for the individual groups of 3D object points, one group for each camera pose with at least one object point imagePointGroups The accessor for the individual groups of 2D image points, one group for each camera pose and one image point for each corresponding object point optimizedCamera The resulting optimized camera profile optimizedPoses Optional accessor for the resulting optimized camera poses, matching with the new camera profile 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) onlyFrontObjectPoints True, to avoid that the optimized 3D position lies behind any camera 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 intermediateErrors Optional resulting intermediate averaged pixel errors for the individual optimization steps, in relation to the defined estimator
- Returns
- True, if succeeded
- See also
- optimizeCameraPoseIF().
◆ optimizeCameraPosesIF()
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static |
Minimizes the projection error between the projections of static 3D object points and their corresponding image points in several 6DOF camera poses.
Beware: The given poses are not equivalent to extrinsic camera matrices.
The given poses must be inverted and flipped around the new x axis by 180 degree.
- See also
- optimizeCameraPose().
The documentation for this class was generated from the following file:
