add binary measurement class
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/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010-2020, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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#pragma once
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/**
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* @file BinaryMeasurement.h
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* @author Akshay Krishnan
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* @date July 2020
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* @brief Binary measurement for representing edges in the epipolar graph
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*/
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#include <gtsam/inference/Key.h>
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#include <gtsam/linear/NoiseModel.h>
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namespace gtsam {
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template<class VALUE>
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class BinaryMeasurement {
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// Check that VALUE type is testable
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BOOST_CONCEPT_ASSERT((IsTestable<VALUE>));
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public:
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typedef VALUE T;
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// shorthand for a smart pointer to a measurement
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typedef typename boost::shared_ptr<BinaryMeasurement> shared_ptr;
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private:
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Key key1_, key2_; /** Keys */
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VALUE measured_; /** The measurement */
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SharedNoiseModel noiseModel_; /** Noise model */
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public:
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/** default constructor - only use for serialization */
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BinaryMeasurement() {}
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/** Constructor */
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BinaryMeasurement(Key key1, Key key2, const VALUE& measured,
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const SharedNoiseModel& model = nullptr) :
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key1_(key1), key2_(key2), measured_(measured), noiseModel_(model) {
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}
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virtual ~BinaryMeasurement() {}
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Key key1() const { return key1_; }
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Key key2() const { return key2_; }
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const SharedNoiseModel& noiseModel() const { return noiseModel_; }
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/** implement functions needed for Testable */
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/** print */
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void print(const std::string& s, const KeyFormatter& keyFormatter = DefaultKeyFormatter) const {
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std::cout << s << "BinaryMeasurement("
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<< keyFormatter(this->key1()) << ","
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<< keyFormatter(this->key2()) << ")\n";
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traits<T>::Print(measured_, " measured: ");
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this->noiseModel_->print(" noise model: ");
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}
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/** equals */
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bool equals(const BetweenMeasurement& expected, double tol=1e-9) const {
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const BetweenMeasurement<VALUE> *e = dynamic_cast<const BetweenMeasurement<VALUE>*> (&expected);
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return e != nullptr && key1_ == expected.key1() &&
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key2_ == expected.key2()
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&& traits<VALUE>::Equals(this->measured_, e->measured_, tol) &&
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noiseModel_.equals(expected.noiseModel());
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}
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/** return the measured */
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const VALUE& measured() const {
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return measured_;
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}
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/** number of variables attached to this measurement */
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std::size_t size() const {
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return 2;
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}
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}; // \class BetweenMeasurement
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}
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@ -36,6 +36,8 @@ namespace gtsam {
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* normalized(Tb - Ta) - w_aZb.point3()
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* normalized(Tb - Ta) - w_aZb.point3()
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*
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*
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* @addtogroup SFM
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* @addtogroup SFM
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*
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*
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*/
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*/
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class TranslationFactor : public NoiseModelFactor2<Point3, Point3> {
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class TranslationFactor : public NoiseModelFactor2<Point3, Point3> {
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private:
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private:
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@ -33,15 +33,12 @@ using namespace gtsam;
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using namespace std;
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using namespace std;
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NonlinearFactorGraph TranslationRecovery::buildGraph() const {
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NonlinearFactorGraph TranslationRecovery::buildGraph() const {
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auto noiseModel = noiseModel::Isotropic::Sigma(3, 0.01);
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NonlinearFactorGraph graph;
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NonlinearFactorGraph graph;
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// Add all relative translation edges
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// Add all relative translation edges
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for (auto edge : relativeTranslations_) {
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for (auto edge : relativeTranslations_) {
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Key a, b;
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graph.emplace_shared<TranslationFactor>(edge.key1(), edge.key2(),
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tie(a, b) = edge.first;
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edge.measured(), edge.noiseModel());
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const Unit3 w_aZb = edge.second;
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graph.emplace_shared<TranslationFactor>(a, b, w_aZb, noiseModel);
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}
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}
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return graph;
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return graph;
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@ -49,14 +46,12 @@ NonlinearFactorGraph TranslationRecovery::buildGraph() const {
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void TranslationRecovery::addPrior(const double scale,
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void TranslationRecovery::addPrior(const double scale,
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NonlinearFactorGraph* graph) const {
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NonlinearFactorGraph* graph) const {
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auto noiseModel = noiseModel::Isotropic::Sigma(3, 0.01);
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//TODO(akshay-krishnan): make this an input argument
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auto priorNoiseModel = noiseModel::Isotropic::Sigma(3, 0.01);
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auto edge = relativeTranslations_.begin();
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auto edge = relativeTranslations_.begin();
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Key a, b;
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graph->emplace_shared<PriorFactor<Point3> >(edge->key1(), Point3(0, 0, 0), priorNoiseModel);
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tie(a, b) = edge->first;
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graph->emplace_shared<PriorFactor<Point3> >(edge->key2(), scale * edge->measured().point3(),
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const Unit3 w_aZb = edge->second;
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edge->noiseModel());
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graph->emplace_shared<PriorFactor<Point3> >(a, Point3(0, 0, 0), noiseModel);
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graph->emplace_shared<PriorFactor<Point3> >(b, scale * w_aZb.point3(),
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noiseModel);
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}
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}
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Values TranslationRecovery::initalizeRandomly() const {
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Values TranslationRecovery::initalizeRandomly() const {
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@ -71,10 +66,8 @@ Values TranslationRecovery::initalizeRandomly() const {
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// Loop over measurements and add a random translation
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// Loop over measurements and add a random translation
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for (auto edge : relativeTranslations_) {
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for (auto edge : relativeTranslations_) {
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Key a, b;
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insert(edge.key1());
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tie(a, b) = edge.first;
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insert(edge.key2());
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insert(a);
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insert(b);
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}
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}
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return initial;
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return initial;
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}
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}
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@ -90,6 +83,7 @@ Values TranslationRecovery::run(const double scale) const {
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TranslationRecovery::TranslationEdges TranslationRecovery::SimulateMeasurements(
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TranslationRecovery::TranslationEdges TranslationRecovery::SimulateMeasurements(
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const Values& poses, const vector<KeyPair>& edges) {
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const Values& poses, const vector<KeyPair>& edges) {
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auto edgeNoiseModel = noiseModel::Isotropic::Sigma(3, 0.01);
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TranslationEdges relativeTranslations;
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TranslationEdges relativeTranslations;
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for (auto edge : edges) {
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for (auto edge : edges) {
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Key a, b;
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Key a, b;
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@ -97,7 +91,7 @@ TranslationRecovery::TranslationEdges TranslationRecovery::SimulateMeasurements(
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const Pose3 wTa = poses.at<Pose3>(a), wTb = poses.at<Pose3>(b);
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const Pose3 wTa = poses.at<Pose3>(a), wTb = poses.at<Pose3>(b);
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const Point3 Ta = wTa.translation(), Tb = wTb.translation();
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const Point3 Ta = wTa.translation(), Tb = wTb.translation();
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const Unit3 w_aZb(Tb - Ta);
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const Unit3 w_aZb(Tb - Ta);
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relativeTranslations[edge] = w_aZb;
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relativeTranslations.emplace_back(a, b, w_aZb, edgeNoiseModel);
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}
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}
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return relativeTranslations;
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return relativeTranslations;
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}
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}
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#include <gtsam/geometry/Unit3.h>
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#include <gtsam/geometry/Unit3.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/sfm/BinaryMeasurement.h>
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#include <map>
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#include <utility>
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#include <utility>
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#include <vector>
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namespace gtsam {
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namespace gtsam {
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@ -48,7 +49,7 @@ namespace gtsam {
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class TranslationRecovery {
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class TranslationRecovery {
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public:
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public:
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using KeyPair = std::pair<Key, Key>;
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using KeyPair = std::pair<Key, Key>;
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using TranslationEdges = std::map<KeyPair, Unit3>;
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using TranslationEdges = std::vector<BinaryMeasurement<Unit3>>;
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private:
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private:
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TranslationEdges relativeTranslations_;
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TranslationEdges relativeTranslations_;
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@ -59,7 +60,8 @@ class TranslationRecovery {
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* @brief Construct a new Translation Recovery object
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* @brief Construct a new Translation Recovery object
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*
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*
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* @param relativeTranslations the relative translations, in world coordinate
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* @param relativeTranslations the relative translations, in world coordinate
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* frames, indexed in a map by a pair of Pose keys.
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* frames, vector of BinaryMeasurements of Unit3, where each key of a measurement
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* is a point in 3D.
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* @param lmParams (optional) gtsam::LavenbergMarquardtParams that can be
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* @param lmParams (optional) gtsam::LavenbergMarquardtParams that can be
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* used to modify the parameters for the LM optimizer. By default, uses the
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* used to modify the parameters for the LM optimizer. By default, uses the
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* default LM parameters.
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* default LM parameters.
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@ -105,8 +107,9 @@ class TranslationRecovery {
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*
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*
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* @param poses SE(3) ground truth poses stored as Values
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* @param poses SE(3) ground truth poses stored as Values
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* @param edges pairs (a,b) for which a measurement w_aZb will be generated.
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* @param edges pairs (a,b) for which a measurement w_aZb will be generated.
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* @return TranslationEdges map from a KeyPair to the simulated Unit3
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* @return TranslationEdges vector of binary measurements where the keys are
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* translation direction measurement between the cameras in KeyPair.
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* the cameras and the measurement is the simulated Unit3 translation
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* direction between the cameras.
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*/
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*/
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static TranslationEdges SimulateMeasurements(
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static TranslationEdges SimulateMeasurements(
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const Values& poses, const std::vector<KeyPair>& edges);
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const Values& poses, const std::vector<KeyPair>& edges);
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/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010-2020, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file testBinaryMeasurement.cpp
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* @brief Unit tests for BinaryMeasurement class
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* @author Akshay Krishnan
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* @date July 2020
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*/
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#include <gtsam/sfm/BinaryMeasurement.h>
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#include <gtsam/geometry/Rot3.h>
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#include <gtsam/geometry/Unit3.h>
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#include <gtsam/geometry/Pose3.h>
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#include <CppUnitLite/TestHarness.h>
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using namespace std;
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using namespace gtsam;
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// Keys are deliberately *not* in sorted order to test that case.
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static const Key kKey1(2), kKey2(1);
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// Create noise models for unit3 and rot3
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static SharedNoiseModel unit3_model(noiseModel::Isotropic::Sigma(2, 0.05));
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static SharedNoiseModel rot3_model(noiseModel::Isotropic::Sigma(3, 0.05));
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const Unit3 unit3Measured(Vector3(1, 1, 1));
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const Rot3 rot3Measured;
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TEST(BinaryMeasurement, Unit3) {
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BinaryMeasurement<Unit3> unit3Measurement(kKey1, kKey2, unit3Measured,
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unit3_model);
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EXPECT_LONGS_EQUAL(unit3Measurement.key1(), kKey1);
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EXPECT_LONGS_EQUAL(unit3Measurement.key2(), kKey2);
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EXPECT(unit3Measurement.measured().equals(unit3Measured));
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}
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TEST(BinaryMeasurement, Rot3) {
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BinaryMeasurement<Rot3> rot3Measurement(kKey1, kKey2, rot3Measured,
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rot3_model);
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EXPECT_LONGS_EQUAL(rot3Measurement.key1(), kKey1);
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EXPECT_LONGS_EQUAL(rot3Measurement.key2(), kKey2);
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EXPECT(rot3Measurement.measured().equals(rot3Measured));
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}
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/* ************************************************************************* */
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int main() {
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TestResult tr;
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return TestRegistry::runAllTests(tr);
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}
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/* ************************************************************************* */
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