Move to its own compilation unit
Frank Dellaert
parent
f4b2b8bde0
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98b8d6b4f3
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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 TranslationRecovery.h
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* @author Frank Dellaert
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* @date March 2020
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* @brief test recovering translations when rotations are given.
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*/
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#include <gtsam/sfm/TranslationRecovery.h>
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#include <gtsam/geometry/Point3.h>
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#include <gtsam/geometry/Pose3.h>
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#include <gtsam/geometry/Unit3.h>
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#include <gtsam/linear/NoiseModel.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/NonlinearFactor.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/sfm/TranslationFactor.h>
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#include <gtsam/slam/PriorFactor.h>
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using namespace gtsam;
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using namespace std;
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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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// Add all relative translation edges
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for (auto edge : relativeTranslations_) {
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Key a, b;
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tie(a, b) = edge.first;
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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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return graph;
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}
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void TranslationRecovery::addPrior(const double scale,
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NonlinearFactorGraph* graph) const {
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auto noiseModel = noiseModel::Isotropic::Sigma(3, 0.01);
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auto edge = relativeTranslations_.begin();
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Key a, b;
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tie(a, b) = edge->first;
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const Unit3 w_aZb = edge->second;
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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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Values TranslationRecovery::initalizeRandomly() const {
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// Create a lambda expression that checks whether value exists and randomly
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// initializes if not.
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Values initial;
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auto insert = [&initial](Key j) {
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if (!initial.exists(j)) {
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initial.insert<Point3>(j, Vector3::Random());
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}
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};
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// Loop over measurements and add a random translation
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for (auto edge : relativeTranslations_) {
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Key a, b;
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tie(a, b) = edge.first;
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insert(a);
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insert(b);
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}
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return initial;
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}
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Values TranslationRecovery::run(const double scale) const {
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auto graph = buildGraph();
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addPrior(scale, &graph);
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const Values initial = initalizeRandomly();
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LevenbergMarquardtOptimizer lm(graph, initial, params_);
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Values result = lm.optimize();
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return result;
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}
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TranslationRecovery::TranslationEdges TranslationRecovery::SimulateMeasurements(
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const Values& poses, const vector<KeyPair>& edges) {
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TranslationEdges relativeTranslations;
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for (auto edge : edges) {
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Key a, b;
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tie(a, b) = edge;
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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 Unit3 w_aZb(Tb - Ta);
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relativeTranslations[edge] = w_aZb;
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}
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return relativeTranslations;
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}
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@ -0,0 +1,108 @@
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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 TranslationRecovery.h
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* @author Frank Dellaert
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* @date March 2020
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* @brief test recovering translations when rotations are given.
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*/
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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/Values.h>
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#include <map>
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#include <utility>
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namespace gtsam {
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// Set up an optimization problem for the unknown translations Ti in the world
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// coordinate frame, given the known camera attitudes wRi with respect to the
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// world frame, and a set of (noisy) translation directions of type Unit3,
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// w_aZb. The measurement equation is
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// w_aZb = Unit3(Tb - Ta) (1)
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// i.e., w_aZb is the translation direction from frame A to B, in world
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// coordinates. Although Unit3 instances live on a manifold, following
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// Wilson14eccv_1DSfM.pdf error we compute the *chordal distance* in the
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// ambient world coordinate frame.
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//
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// It is clear that we cannot recover the scale, nor the absolute position,
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// so the gauge freedom in this case is 3 + 1 = 4. We fix these by taking fixing
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// the translations Ta and Tb associated with the first measurement w_aZb,
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// clamping them to their initial values as given to this method. If no initial
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// values are given, we use the origin for Tb and set Tb to make (1) come
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// through, i.e.,
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// Tb = s * wRa * Point3(w_aZb) (2)
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// where s is an arbitrary scale that can be supplied, default 1.0. Hence, two
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// versions are supplied below corresponding to whether we have initial values
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// or not.
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class TranslationRecovery {
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public:
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using KeyPair = std::pair<Key, Key>;
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using TranslationEdges = std::map<KeyPair, Unit3>;
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private:
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TranslationEdges relativeTranslations_;
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LevenbergMarquardtParams params_;
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public:
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/**
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* @brief Construct a new Translation Recovery object
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*
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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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*/
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TranslationRecovery(const TranslationEdges& relativeTranslations)
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: relativeTranslations_(relativeTranslations) {
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params_.setVerbosityLM("Summary");
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}
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/**
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* @brief Build the factor graph to do the optimization.
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*
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* @return NonlinearFactorGraph
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*/
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NonlinearFactorGraph buildGraph() const;
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/**
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* @brief Add priors on ednpoints of first measurement edge.
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*
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* @param scale scale for first relative translation which fixes gauge.
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* @param graph factor graph to which prior is added.
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*/
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void addPrior(const double scale, NonlinearFactorGraph* graph) const;
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/**
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* @brief Create random initial translations.
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*
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* @return Values
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*/
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Values initalizeRandomly() const;
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/**
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* @brief Build and optimize factor graph.
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*
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* @param scale scale for first relative translation which fixes gauge.
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* @return Values
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*/
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Values run(const double scale = 1.0) const;
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/**
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* @brief Simulate translation direction measurements
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*
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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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*/
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static TranslationEdges SimulateMeasurements(
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const Values& poses, const std::vector<KeyPair>& edges);
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};
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} // namespace gtsam
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@ -1,177 +1,6 @@
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/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, 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 TranslationRecovery.h
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* @author Frank Dellaert
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* @date March 2020
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* @brief test recovering translations when rotations are given.
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*/
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#include <gtsam/geometry/Point3.h>
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#include <gtsam/geometry/Pose3.h>
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#include <gtsam/geometry/Unit3.h>
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/linear/NoiseModel.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/NonlinearFactor.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/sfm/TranslationFactor.h>
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#include <gtsam/slam/PriorFactor.h>
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namespace gtsam {
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// Set up an optimization problem for the unknown translations Ti in the world
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// coordinate frame, given the known camera attitudes wRi with respect to the
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// world frame, and a set of (noisy) translation directions of type Unit3,
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// w_aZb. The measurement equation is
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// w_aZb = Unit3(Tb - Ta) (1)
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// i.e., w_aZb is the translation direction from frame A to B, in world
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// coordinates. Although Unit3 instances live on a manifold, following
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// Wilson14eccv_1DSfM.pdf error we compute the *chordal distance* in the
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// ambient world coordinate frame.
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//
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// It is clear that we cannot recover the scale, nor the absolute position,
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// so the gauge freedom in this case is 3 + 1 = 4. We fix these by taking fixing
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// the translations Ta and Tb associated with the first measurement w_aZb,
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// clamping them to their initial values as given to this method. If no initial
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// values are given, we use the origin for Tb and set Tb to make (1) come
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// through, i.e.,
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// Tb = s * wRa * Point3(w_aZb) (2)
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// where s is an arbitrary scale that can be supplied, default 1.0. Hence, two
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// versions are supplied below corresponding to whether we have initial values
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// or not. Because the latter one is called from the first one, this is prime.
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class TranslationRecovery {
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public:
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using KeyPair = std::pair<Key, Key>;
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using TranslationEdges = std::map<KeyPair, Unit3>;
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private:
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TranslationEdges relativeTranslations_;
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LevenbergMarquardtParams params_;
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public:
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/**
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* @brief Construct a new Translation Recovery object
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*
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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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*/
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TranslationRecovery(const TranslationEdges& relativeTranslations)
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: relativeTranslations_(relativeTranslations) {
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params_.setVerbosityLM("Summary");
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}
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/**
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* @brief Build the factor graph to do the optimization.
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*
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* @return NonlinearFactorGraph
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*/
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NonlinearFactorGraph buildGraph() const {
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auto noiseModel = noiseModel::Isotropic::Sigma(3, 0.01);
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NonlinearFactorGraph graph;
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// Add all relative translation edges
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for (auto edge : relativeTranslations_) {
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Key a, b;
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std::tie(a, b) = edge.first;
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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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return graph;
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}
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/**
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* @brief Add priors on ednpoints of first measurement edge.
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*
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* @param scale scale for first relative translation which fixes gauge.
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* @param graph factor graph to which prior is added.
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*/
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void addPrior(const double scale, NonlinearFactorGraph* graph) const {
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auto noiseModel = noiseModel::Isotropic::Sigma(3, 0.01);
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auto edge = relativeTranslations_.begin();
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Key a, b;
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std::tie(a, b) = edge->first;
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const Unit3 w_aZb = edge->second;
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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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* @brief Create random initial translations.
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*
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* @return Values
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*/
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Values initalizeRandomly() const {
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Values initial;
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auto insert = [&initial](Key j) {
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if (!initial.exists(j)) {
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initial.insert<Point3>(j, Vector3::Random());
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}
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};
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// Loop over measurements and add a random translation
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for (auto edge : relativeTranslations_) {
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Key a, b;
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std::tie(a, b) = edge.first;
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insert(a);
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insert(b);
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}
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return initial;
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}
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/**
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* @brief Build and optimize factor graph.
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*
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* @param scale scale for first relative translation which fixes gauge.
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* @return Values
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*/
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Values run(const double scale = 1.0) const {
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auto graph = buildGraph();
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addPrior(scale, &graph);
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const Values initial = initalizeRandomly();
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LevenbergMarquardtOptimizer lm(graph, initial, params_);
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Values result = lm.optimize();
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return result;
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}
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/**
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* @brief Simulate translation direction measurements
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*
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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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*/
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static TranslationEdges SimulateMeasurements(
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const Values& poses, const std::vector<KeyPair>& edges) {
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TranslationEdges relativeTranslations;
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for (auto edge : edges) {
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Key a, b;
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std::tie(a, b) = edge;
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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 Unit3 w_aZb(Tb - Ta);
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relativeTranslations[edge] = w_aZb;
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}
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return relativeTranslations;
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}
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};
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} // namespace gtsam
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/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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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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@ -187,6 +16,8 @@ class TranslationRecovery {
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* @brief test recovering translations when rotations are given.
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*/
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#include <gtsam/sfm/TranslationRecovery.h>
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#include <CppUnitLite/TestHarness.h>
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#include <gtsam/slam/dataset.h>
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