1. Default linear solver is Eigen::LDLT
2. Options::max_iterations -> Options::max_num_iterations
3. Options::error_threshold -> Options::cost_threshold
4. Options::relative_step_threshold -> Options::parameter_threshold
5. Options::initial_scale_factor -> Options::initial_trust_region_radius
6. The default values of the above parameters have been changed
to match those in ceres::Solver::Options
7. Status::RUNNING has been removed
8. Update now returns a bool instead of a Status enum and
the status handling has been included in the main loop.
9. Summary::gradient_norm has been changed to Summary::gradient_max_norm
to match the convergence test
10. A member variable cost_ has been added which is computed by Update
11. The test for parameter_tolerance based convergence is made
more robust near zero.
12. Use of double has been replaced by Scalar.
13. Minor clang-formatting
Change-Id: I3cb0e2fd0a0204476bb8718761dc740cdf5e42ce
The solver code must rely on the vectors for
sizing, since not all cost functions will have
NumParameters() or NumResiduals().
Change-Id: Id254ce37507443910edb0064de7907d64558851e
1. Default constructor and initialization for Summary.
2. Add Jacobi scaling.
3. Add bounds on the lm diagonal
4. Use the diagonal of J'J as the regularizer instead of identity.
5. Update the computation of rho to match the change in regularization.
As a result of these changes, the performance of TinySolver is
now the same as ceres::Solver, solving 53 out of 54 problems.
Change-Id: Ie08c3389ac2e3964ffa04411734c06b65835358a
1. Instead of Core/LU just include Eigen/Dense
2. Rename SolverParameters to Options and params to options.
3. Rename Results to Summary.
4. Summary::error_magnitude -> Summary::final_cost.
5. Add Summary::initial_cost.
6. Change definitions of Summary::initial_cost and Summary::final_cost
to match those used by Ceres::Solver.
Change-Id: Id64b78398f47810ca25938a15423c514fc8c164d
1. Change the ordering from NUM_PARAMETERS, NUM_RESIDUALS to
NUM_RESIDUALS, NUM_PARAMETERS in docs and in code.
2. TinySolver::solve -> TinySolver::Solve
Change-Id: I4dca87b971fd9168f1200b53c362669cffc82c1b
Tiny solver is targeted towards small dense least square
solves, where the overhead of calling normal Ceres is too
high. For example, when solving for inverse camera
distortion for every pixel location in a many-megapixel
image. Anecdotally, at one point in the past, tiny solver
was ~20x faster than Ceres for the problems it's intended
for. This is due to two key aspects:
1. Memory is allocated up front: repeated solves incur no
allocation overhead beyond a few scalars on the stack.
2. The cost function is fully inlined into the solver
loop, removing even the cost function call overhead.
Tiny solver originated many years ago as part of
libmv/Blender, where it is still used for distortion solving
today, but the time has come for it to migrate into Ceres.
This commit is just the initial import into Ceres. Follow
up patches will add further cleanups, and add CostFunction
and Jet adapters to make it easier to call tiny solver
(though by using adapters, some performance advantages will
be lost).
Change-Id: I8079535cd41382b1e0ac0ca2fca141711c72b7f8
Sameer Agarwal