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residual[0] = x / z - T(xl);
residual[1] = y / z - T(yl);transformed[1] += b;I have not tried to run the example exactly. I’m essentially trying to load my feature points into the solver, which is configured, as in the example.
FullReport() output:
Solver Summary (v 1.12.0-eigen-(3.2.9)-lapack-suitesparse-(4.5.0)-openmp)
Original Reduced
Parameter blocks 4496 4496
Parameters 13489 13489
Residual blocks 4495 4495
Residual 17980 17980
Minimizer TRUST_REGION
Sparse linear algebra library SUITE_SPARSE
Trust region strategy LEVENBERG_MARQUARDT
Given Used
Linear solver SPARSE_SCHUR SPARSE_SCHUR
Threads 4 4
Linear solver threads 4 4
Linear solver ordering AUTOMATIC 4495, 1
Use inner iterations True True
Inner iteration ordering 4495, 1 4495, 1
Cost:
Initial 2.179317e+002
Final 3.356981e+001
Change 1.843619e+002
Minimizer iterations 17
Successful steps 9
Unsuccessful steps 8
Steps with inner iterations 11
Line search steps 108
Time (in seconds):
Preprocessor 1.1566
Residual evaluation 0.1248
Line search cost evaluation 0.0000
Jacobian evaluation 0.3045
Line search gradient evaluation 0.2811
Linear solver 1.2105
Inner iterations 17.0584
Line search polynomial minimization 0.0173
Minimizer 18.6622
Postprocessor 0.0005
Total 19.8194
Termination: CONVERGENCE (Parameter tolerance reached. Relative step_norm: 4.554931e-011 <= 1.000000e-010.)
Initialization is 0 for all 4 camera params that I use, and initial coordinates are (0, 0, 10), which should be in front of the camera.
Limits are: -0.1 to 0.1 for camera params, and z > 1.0
суббота, 20 августа 2016 г., 23:22:40 UTC+3 пользователь Keir Mierle написал: