79 lines
3.1 KiB
C
79 lines
3.1 KiB
C
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// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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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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// Cost term that implements a prior on a parameter block using a
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// normal distribution.
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#ifndef CERES_PUBLIC_NORMAL_PRIOR_H_
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#define CERES_PUBLIC_NORMAL_PRIOR_H_
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#include "ceres/cost_function.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/internal/disable_warnings.h"
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namespace ceres {
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// Implements a cost function of the form
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//
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// cost(x) = ||A(x - b)||^2
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//
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// where, the matrix A and the vector b are fixed and x is the
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// variable. In case the user is interested in implementing a cost
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// function of the form
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//
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// cost(x) = (x - mu)^T S^{-1} (x - mu)
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//
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// where, mu is a vector and S is a covariance matrix, then, A =
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// S^{-1/2}, i.e the matrix A is the square root of the inverse of the
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// covariance, also known as the stiffness matrix. There are however
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// no restrictions on the shape of A. It is free to be rectangular,
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// which would be the case if the covariance matrix S is rank
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// deficient.
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class CERES_EXPORT NormalPrior: public CostFunction {
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public:
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// Check that the number of rows in the vector b are the same as the
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// number of columns in the matrix A, crash otherwise.
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NormalPrior(const Matrix& A, const Vector& b);
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virtual bool Evaluate(double const* const* parameters,
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double* residuals,
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double** jacobians) const;
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private:
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Matrix A_;
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Vector b_;
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};
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} // namespace ceres
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#include "ceres/internal/reenable_warnings.h"
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#endif // CERES_PUBLIC_NORMAL_PRIOR_H_
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