| Enumerator |
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| None | |
| UseFusedDepth | Should the algorithm work on the ray depth image (0) or the fused depth (1) (unsigned,[0,-]:0, RW)
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| SolveFull | This option configures the internal solver to estimate all parameters at once, else the solver estimates 5 groups of parameters subsequently. First the lens vertex then the beam radius, after that the wavefront and lastly the MLA Residual polynomials. To refine the calibration a full calibration is done after the separate group calibration. Therefore activating this option leads to a much faster calibration process. (unsigned,[0,-]:0, RW)
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| AdaptPlaneDistance | If the adapt plane distance option is activated, the plane is adjusted with each iteration regarding its distance but not regarding its orientation. (unsigned,[0,1]:1, RW)
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| CheckGradiantsWhileIteration | Check gradients while iteration. Activating this option can lead to better results. By activating this option the calibration will be much slower. (unsigned,[0,-]:0, RW)
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| MinimizerType | Which minimizer should be used in the internal solver 0 = Trust region , 1 = Line search. Trust Region The trust region approach approximates the objective function using using a model function (often a quadratic) over a subset of the search space known as the trust region. If the model function succeeds in minimizing the true objective function the trust region is expanded; conversely, otherwise it is contracted and the model optimization problem is solved again.
Line Search The line search approach first finds a descent direction along which the objective function will be reduced and then computes a step size that decides how far should move along that direction.The descent direction can be computed by various methods, such as gradient descent, Newton's method and Quasi - Newton method.The step size can be determined either exactly or inexactly. (unsigned,[0,-]:0, RW)
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| Strategy | Which minimizer should be used in the internal solver 0 = Levenberg Marquardt , 1 = dogleg Levenberg-Marquardt The Levenberg - Marquardt algorithm[Levenberg][Marquardt] is the most popular algorithm for solving non - linear least squares problems.It was also the first trust region algorithm to be developed[Levenberg][Marquardt]. Dogleg Another strategy for solving the trust region problem(3) was introduced by M.J.D.Powell.The key idea there is to compute two vectors. (unsigned,[0,-]:0, RW)
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| SolverType | These solvers are for general rectangular systems formed from the normal equations A'A x = A'b. They are direct solvers and do not assume any special problem structure. Solve the normal equations using a dense Cholesky solver; based on Eigen. DENSE_NORMAL_CHOLESKY (0) Solve the normal equations using a dense QR solver; based on Eigen. DENSE_QR (1) Solve the normal equations using a sparse cholesky solver; requires SuiteSparse or CXSparse. SPARSE_NORMAL_CHOLESKY (2)
Specialized solvers, specific to problems with a generalized bi-partitite structure.
Solves the reduced linear system using a dense Cholesky solver; based on Eigen. DENSE_SCHUR (3)
Solves the reduced linear system using a sparse Cholesky solver; based on CHOLMOD. SPARSE_SCHUR(4)
Solves the reduced linear system using Conjugate Gradients, based on a new Ceres implementation. Suitable for large scale problems.
ITERATIVE_SCHUR (5)
Conjugate gradients on the normal equations. CGNR (6) (unsigned,[0,6]:1, RW)
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| MaxIterations | Number of calibration iterations. (unsigned,[0,200]:100, RW)
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| EnableIntermediateIteration | Setting "EnableIntermediateIteration" to 1 enables the use of a non-linear generalization Algorithm. This version has a higher iteration complexity, but also displays better convergence behavior per iteration. By activating this option the calibration will be much slower. (unsigned,[0,-]:0, RW)
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| CalibrateLensTransitions | This enables the calibration of lens transitions. (Experimental) (unsigned,[0,-]:0, RW)
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| LensDistortionVertexParameterScale | How much should the lens distortion vertex adjustment be scaled. (unsigned,[0,100000000]:10000, RW)
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| BeamCorrectionParameterScale | How much should the beam correction adjustment be scaled. (unsigned,[0,100000000]:1000, RW)
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| WavefrontAberrationScale | How much should the wavefront aberration correction adjustment be scaled. (unsigned,[0,100000000]:10000, RW)
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| LensDepthParameterScale | How much should the lens depth polynomial parameter adjustment be scaled. (unsigned,[0,100000000]:1000, RW)
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| LeftOverErrorParameterScale | How much should the lens complete radial polynomial parameter adjustment be scaled. (unsigned,[0,100000000]:10000, RW)
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| LensTransitionScale | How much should the lens transition adjustment be scaled. (unsigned,[0,100000000]:1000000, RW)
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1.8.18