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Diffstat (limited to 'extern/libmv/third_party/ceres/internal/ceres/corrector.cc')
| -rw-r--r-- | extern/libmv/third_party/ceres/internal/ceres/corrector.cc | 158 |
1 files changed, 0 insertions, 158 deletions
diff --git a/extern/libmv/third_party/ceres/internal/ceres/corrector.cc b/extern/libmv/third_party/ceres/internal/ceres/corrector.cc deleted file mode 100644 index 581fc6d4fc0..00000000000 --- a/extern/libmv/third_party/ceres/internal/ceres/corrector.cc +++ /dev/null @@ -1,158 +0,0 @@ -// Ceres Solver - A fast non-linear least squares minimizer -// Copyright 2010, 2011, 2012 Google Inc. All rights reserved. -// http://code.google.com/p/ceres-solver/ -// -// Redistribution and use in source and binary forms, with or without -// modification, are permitted provided that the following conditions are met: -// -// * Redistributions of source code must retain the above copyright notice, -// this list of conditions and the following disclaimer. -// * Redistributions in binary form must reproduce the above copyright notice, -// this list of conditions and the following disclaimer in the documentation -// and/or other materials provided with the distribution. -// * Neither the name of Google Inc. nor the names of its contributors may be -// used to endorse or promote products derived from this software without -// specific prior written permission. -// -// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE -// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE -// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR -// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF -// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS -// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN -// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) -// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE -// POSSIBILITY OF SUCH DAMAGE. -// -// Author: sameeragarwal@google.com (Sameer Agarwal) - -#include "ceres/corrector.h" - -#include <cstddef> -#include <cmath> -#include "ceres/internal/eigen.h" -#include "glog/logging.h" - -namespace ceres { -namespace internal { - -Corrector::Corrector(const double sq_norm, const double rho[3]) { - CHECK_GE(sq_norm, 0.0); - sqrt_rho1_ = sqrt(rho[1]); - - // If sq_norm = 0.0, the correction becomes trivial, the residual - // and the jacobian are scaled by the squareroot of the derivative - // of rho. Handling this case explicitly avoids the divide by zero - // error that would occur below. - // - // The case where rho'' < 0 also gets special handling. Technically - // it shouldn't, and the computation of the scaling should proceed - // as below, however we found in experiments that applying the - // curvature correction when rho'' < 0, which is the case when we - // are in the outlier region slows down the convergence of the - // algorithm significantly. - // - // Thus, we have divided the action of the robustifier into two - // parts. In the inliner region, we do the full second order - // correction which re-wights the gradient of the function by the - // square root of the derivative of rho, and the Gauss-Newton - // Hessian gets both the scaling and the rank-1 curvature - // correction. Normaly, alpha is upper bounded by one, but with this - // change, alpha is bounded above by zero. - // - // Empirically we have observed that the full Triggs correction and - // the clamped correction both start out as very good approximations - // to the loss function when we are in the convex part of the - // function, but as the function starts transitioning from convex to - // concave, the Triggs approximation diverges more and more and - // ultimately becomes linear. The clamped Triggs model however - // remains quadratic. - // - // The reason why the Triggs approximation becomes so poor is - // because the curvature correction that it applies to the gauss - // newton hessian goes from being a full rank correction to a rank - // deficient correction making the inversion of the Hessian fraught - // with all sorts of misery and suffering. - // - // The clamped correction retains its quadratic nature and inverting it - // is always well formed. - if ((sq_norm == 0.0) || (rho[2] <= 0.0)) { - residual_scaling_ = sqrt_rho1_; - alpha_sq_norm_ = 0.0; - return; - } - - // We now require that the first derivative of the loss function be - // positive only if the second derivative is positive. This is - // because when the second derivative is non-positive, we do not use - // the second order correction suggested by BANS and instead use a - // simpler first order strategy which does not use a division by the - // gradient of the loss function. - CHECK_GT(rho[1], 0.0); - - // Calculate the smaller of the two solutions to the equation - // - // 0.5 * alpha^2 - alpha - rho'' / rho' * z'z = 0. - // - // Start by calculating the discriminant D. - const double D = 1.0 + 2.0 * sq_norm * rho[2] / rho[1]; - - // Since both rho[1] and rho[2] are guaranteed to be positive at - // this point, we know that D > 1.0. - - const double alpha = 1.0 - sqrt(D); - - // Calculate the constants needed by the correction routines. - residual_scaling_ = sqrt_rho1_ / (1 - alpha); - alpha_sq_norm_ = alpha / sq_norm; -} - -void Corrector::CorrectResiduals(const int num_rows, double* residuals) { - DCHECK(residuals != NULL); - // Equation 11 in BANS. - VectorRef(residuals, num_rows) *= residual_scaling_; -} - -void Corrector::CorrectJacobian(const int num_rows, - const int num_cols, - double* residuals, - double* jacobian) { - DCHECK(residuals != NULL); - DCHECK(jacobian != NULL); - - // The common case (rho[2] <= 0). - if (alpha_sq_norm_ == 0.0) { - VectorRef(jacobian, num_rows * num_cols) *= sqrt_rho1_; - return; - } - - // Equation 11 in BANS. - // - // J = sqrt(rho) * (J - alpha^2 r * r' J) - // - // In days gone by this loop used to be a single Eigen expression of - // the form - // - // J = sqrt_rho1_ * (J - alpha_sq_norm_ * r* (r.transpose() * J)); - // - // Which turns out to about 17x slower on bal problems. The reason - // is that Eigen is unable to figure out that this expression can be - // evaluated columnwise and ends up creating a temporary. - for (int c = 0; c < num_cols; ++c) { - double r_transpose_j = 0.0; - for (int r = 0; r < num_rows; ++r) { - r_transpose_j += jacobian[r * num_cols + c] * residuals[r]; - } - - for (int r = 0; r < num_rows; ++r) { - jacobian[r * num_cols + c] = sqrt_rho1_ * - (jacobian[r * num_cols + c] - - alpha_sq_norm_ * residuals[r] * r_transpose_j); - } - } -} - -} // namespace internal -} // namespace ceres |