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https://github.com/ceres-solver/ceres-solver.git
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d05515b3eb
Binary operations between Jets and doubles are well defined and should not require an explicit conversion to Jets to work. This was an oversight earlier and lead to overzealous conversions all over our in our example code. Change-Id: I1799770818e136edfc0a5802d86037ce9aec4923
178 lines
6.9 KiB
C++
178 lines
6.9 KiB
C++
// 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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// Templated struct implementing the camera model and residual
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// computation for bundle adjustment used by Noah Snavely's Bundler
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// SfM system. This is also the camera model/residual for the bundle
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// adjustment problems in the BAL dataset. It is templated so that we
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// can use Ceres's automatic differentiation to compute analytic
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// jacobians.
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//
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// For details see: http://phototour.cs.washington.edu/bundler/
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// and http://grail.cs.washington.edu/projects/bal/
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#ifndef CERES_EXAMPLES_SNAVELY_REPROJECTION_ERROR_H_
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#define CERES_EXAMPLES_SNAVELY_REPROJECTION_ERROR_H_
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#include "ceres/rotation.h"
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namespace ceres {
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namespace examples {
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// Templated pinhole camera model for used with Ceres. The camera is
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// parameterized using 9 parameters: 3 for rotation, 3 for translation, 1 for
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// focal length and 2 for radial distortion. The principal point is not modeled
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// (i.e. it is assumed be located at the image center).
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struct SnavelyReprojectionError {
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SnavelyReprojectionError(double observed_x, double observed_y)
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: observed_x(observed_x), observed_y(observed_y) {}
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template <typename T>
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bool operator()(const T* const camera,
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const T* const point,
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T* residuals) const {
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// camera[0,1,2] are the angle-axis rotation.
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T p[3];
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AngleAxisRotatePoint(camera, point, p);
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// camera[3,4,5] are the translation.
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p[0] += camera[3];
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p[1] += camera[4];
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p[2] += camera[5];
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// Compute the center of distortion. The sign change comes from
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// the camera model that Noah Snavely's Bundler assumes, whereby
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// the camera coordinate system has a negative z axis.
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const T xp = - p[0] / p[2];
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const T yp = - p[1] / p[2];
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// Apply second and fourth order radial distortion.
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const T& l1 = camera[7];
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const T& l2 = camera[8];
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const T r2 = xp*xp + yp*yp;
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const T distortion = 1.0 + r2 * (l1 + l2 * r2);
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// Compute final projected point position.
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const T& focal = camera[6];
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const T predicted_x = focal * distortion * xp;
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const T predicted_y = focal * distortion * yp;
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// The error is the difference between the predicted and observed position.
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residuals[0] = predicted_x - observed_x;
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residuals[1] = predicted_y - observed_y;
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return true;
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}
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// Factory to hide the construction of the CostFunction object from
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// the client code.
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static ceres::CostFunction* Create(const double observed_x,
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const double observed_y) {
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return (new ceres::AutoDiffCostFunction<SnavelyReprojectionError, 2, 9, 3>(
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new SnavelyReprojectionError(observed_x, observed_y)));
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}
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double observed_x;
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double observed_y;
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};
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// Templated pinhole camera model for used with Ceres. The camera is
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// parameterized using 10 parameters. 4 for rotation, 3 for
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// translation, 1 for focal length and 2 for radial distortion. The
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// principal point is not modeled (i.e. it is assumed be located at
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// the image center).
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struct SnavelyReprojectionErrorWithQuaternions {
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// (u, v): the position of the observation with respect to the image
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// center point.
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SnavelyReprojectionErrorWithQuaternions(double observed_x, double observed_y)
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: observed_x(observed_x), observed_y(observed_y) {}
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template <typename T>
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bool operator()(const T* const camera,
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const T* const point,
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T* residuals) const {
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// camera[0,1,2,3] is are the rotation of the camera as a quaternion.
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//
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// We use QuaternionRotatePoint as it does not assume that the
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// quaternion is normalized, since one of the ways to run the
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// bundle adjuster is to let Ceres optimize all 4 quaternion
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// parameters without a local parameterization.
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T p[3];
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QuaternionRotatePoint(camera, point, p);
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p[0] += camera[4];
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p[1] += camera[5];
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p[2] += camera[6];
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// Compute the center of distortion. The sign change comes from
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// the camera model that Noah Snavely's Bundler assumes, whereby
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// the camera coordinate system has a negative z axis.
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const T xp = - p[0] / p[2];
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const T yp = - p[1] / p[2];
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// Apply second and fourth order radial distortion.
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const T& l1 = camera[8];
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const T& l2 = camera[9];
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const T r2 = xp*xp + yp*yp;
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const T distortion = 1.0 + r2 * (l1 + l2 * r2);
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// Compute final projected point position.
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const T& focal = camera[7];
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const T predicted_x = focal * distortion * xp;
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const T predicted_y = focal * distortion * yp;
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// The error is the difference between the predicted and observed position.
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residuals[0] = predicted_x - observed_x;
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residuals[1] = predicted_y - observed_y;
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return true;
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}
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// Factory to hide the construction of the CostFunction object from
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// the client code.
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static ceres::CostFunction* Create(const double observed_x,
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const double observed_y) {
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return (new ceres::AutoDiffCostFunction<
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SnavelyReprojectionErrorWithQuaternions, 2, 10, 3>(
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new SnavelyReprojectionErrorWithQuaternions(observed_x,
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observed_y)));
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}
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double observed_x;
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double observed_y;
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};
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} // namespace examples
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} // namespace ceres
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#endif // CERES_EXAMPLES_SNAVELY_REPROJECTION_ERROR_H_
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