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ceres-solver and colmap
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// Copyright (c) 2022, ETH Zurich and UNC Chapel Hill.
// All rights reserved.
//
// 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 ETH Zurich and UNC Chapel Hill 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 HOLDERS 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
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// POSSIBILITY OF SUCH DAMAGE.
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// Author: Johannes L. Schoenberger (jsch-at-demuc-dot-de)
#include "estimators/triangulation.h"
#include <Eigen/Geometry>
#include "base/projection.h"
#include "base/triangulation.h"
#include "estimators/essential_matrix.h"
#include "optim/combination_sampler.h"
#include "optim/loransac.h"
#include "util/logging.h"
#include "util/math.h"
namespace colmap {
void TriangulationEstimator::SetMinTriAngle(const double min_tri_angle) {
CHECK_GE(min_tri_angle, 0);
min_tri_angle_ = min_tri_angle;
}
void TriangulationEstimator::SetResidualType(const ResidualType residual_type) {
residual_type_ = residual_type;
}
std::vector<TriangulationEstimator::M_t> TriangulationEstimator::Estimate(
const std::vector<X_t>& point_data,
const std::vector<Y_t>& pose_data) const {
CHECK_GE(point_data.size(), 2);
CHECK_EQ(point_data.size(), pose_data.size());
if (point_data.size() == 2) {
// Two-view triangulation.
const M_t xyz = TriangulatePoint(
pose_data[0].proj_matrix, pose_data[1].proj_matrix,
point_data[0].point_normalized, point_data[1].point_normalized);
if (HasPointPositiveDepth(pose_data[0].proj_matrix, xyz) &&
HasPointPositiveDepth(pose_data[1].proj_matrix, xyz) &&
CalculateTriangulationAngle(pose_data[0].proj_center,
pose_data[1].proj_center,
xyz) >= min_tri_angle_) {
return std::vector<M_t>{xyz};
}
} else {
// Multi-view triangulation.
std::vector<Eigen::Matrix3x4d> proj_matrices;
proj_matrices.reserve(point_data.size());
std::vector<Eigen::Vector2d> points;
points.reserve(point_data.size());
for (size_t i = 0; i < point_data.size(); ++i) {
proj_matrices.push_back(pose_data[i].proj_matrix);
points.push_back(point_data[i].point_normalized);
}
const M_t xyz = TriangulateMultiViewPoint(proj_matrices, points);
// Check for cheirality constraint.
for (const auto& pose : pose_data) {
if (!HasPointPositiveDepth(pose.proj_matrix, xyz)) {
return std::vector<M_t>();
}
}
// Check for sufficient triangulation angle.
for (size_t i = 0; i < pose_data.size(); ++i) {
for (size_t j = 0; j < i; ++j) {
const double tri_angle = CalculateTriangulationAngle(
pose_data[i].proj_center, pose_data[j].proj_center, xyz);
if (tri_angle >= min_tri_angle_) {
return std::vector<M_t>{xyz};
}
}
}
}
return std::vector<M_t>();
}
void TriangulationEstimator::Residuals(const std::vector<X_t>& point_data,
const std::vector<Y_t>& pose_data,
const M_t& xyz,
std::vector<double>* residuals) const {
CHECK_EQ(point_data.size(), pose_data.size());
residuals->resize(point_data.size());
for (size_t i = 0; i < point_data.size(); ++i) {
if (residual_type_ == ResidualType::REPROJECTION_ERROR) {
(*residuals)[i] = CalculateSquaredReprojectionError(
point_data[i].point, xyz, pose_data[i].proj_matrix,
*pose_data[i].camera);
} else if (residual_type_ == ResidualType::ANGULAR_ERROR) {
const double angular_error = CalculateNormalizedAngularError(
point_data[i].point_normalized, xyz, pose_data[i].proj_matrix);
(*residuals)[i] = angular_error * angular_error;
}
}
}
bool EstimateTriangulation(
const EstimateTriangulationOptions& options,
const std::vector<TriangulationEstimator::PointData>& point_data,
const std::vector<TriangulationEstimator::PoseData>& pose_data,
std::vector<char>* inlier_mask, Eigen::Vector3d* xyz) {
CHECK_NOTNULL(inlier_mask);
CHECK_NOTNULL(xyz);
CHECK_GE(point_data.size(), 2);
CHECK_EQ(point_data.size(), pose_data.size());
options.Check();
// Robustly estimate track using LORANSAC.
LORANSAC<TriangulationEstimator, TriangulationEstimator,
InlierSupportMeasurer, CombinationSampler>
ransac(options.ransac_options);
ransac.estimator.SetMinTriAngle(options.min_tri_angle);
ransac.estimator.SetResidualType(options.residual_type);
ransac.local_estimator.SetMinTriAngle(options.min_tri_angle);
ransac.local_estimator.SetResidualType(options.residual_type);
const auto report = ransac.Estimate(point_data, pose_data);
if (!report.success) {
return false;
}
*inlier_mask = report.inlier_mask;
*xyz = report.model;
return report.success;
}
} // namespace colmap