mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 08:34:37 +08:00
Sameer Agarwal
07f208fd6d
Remove the Eigen temporary by revealing the columnwise nature of the computation. This also allows us to get rid of the special case for nrow = 1. On problem-356-226730-pre.txt with -robustify evaluation times change from: Before: Residual Evaluations 1.015 Jacobian Evaluations 18.313 After: Residual Evaluations 1.005 Jacobian Evaluations 8.382 To give a sense of the overhead reduction, compare these numbers when loss functions are disabled. Residual Evaluations 0.955 Jacobian Evaluations 7.772 So, this is a 17.5x speedup! The one dimensional specialization was motivated by denoising.cc. The evaluation times there are essentially unchanged. Before: Residual Evaluations 2.774 Jacobian Evaluations 20.178 After: Residual Evaluations 2.588 Jacobian Evaluations 19.781 Change-Id: Ic0efbaed75fe4489635039f17189ae24b97802c8
91 lines
3.9 KiB
C++
91 lines
3.9 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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//
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// Class definition for the object that is responsible for applying a
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// second order correction to the Gauss-Newton based on the ideas in
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// BANS by Triggs et al.
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#ifndef CERES_INTERNAL_CORRECTOR_H_
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#define CERES_INTERNAL_CORRECTOR_H_
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namespace ceres {
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namespace internal {
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// Corrector is responsible for applying the second order correction
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// to the residual and jacobian of a least squares problem based on a
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// radial robust loss.
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//
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// The key idea here is to look at the expressions for the robustified
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// gauss newton approximation and then take its squareroot to get the
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// corresponding corrections to the residual and jacobian. For the
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// full expressions see Eq. 10 and 11 in BANS by Triggs et al.
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class Corrector {
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public:
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// The constructor takes the squared norm, the value, the first and
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// second derivatives of the LossFunction. It precalculates some of
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// the constants that are needed to apply the correction. The
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// correction constant alpha is constrained to be smaller than 1, if
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// it becomes larger than 1, then it will reverse the sign of the
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// residual and the correction. If alpha is equal to 1 will result
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// in a divide by zero error. Thus we constrain alpha to be upper
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// bounded by 1 - epsilon_.
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//
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// rho[1] needs to be positive. The constructor will crash if this
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// condition is not met.
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//
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// In practical use CorrectJacobian should always be called before
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// CorrectResidual, because the jacobian correction depends on the
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// value of the uncorrected residual values.
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explicit Corrector(double sq_norm, const double rho[3]);
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// residuals *= sqrt(rho[1]) / (1 - alpha)
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void CorrectResiduals(int num_rows, double* residuals);
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// jacobian = sqrt(rho[1]) * jacobian -
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// sqrt(rho[1]) * alpha / sq_norm * residuals residuals' * jacobian.
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//
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// The method assumes that the jacobian has row-major storage. It is
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// the caller's responsibility to ensure that the pointer to
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// jacobian is not null.
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void CorrectJacobian(int num_rows,
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int num_cols,
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double* residuals,
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double* jacobian);
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private:
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double sqrt_rho1_;
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double residual_scaling_;
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double alpha_sq_norm_;
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};
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} // namespace internal
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} // namespace ceres
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#endif // CERES_INTERNAL_CORRECTOR_H_
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