99 lines
3.4 KiB
C++
99 lines
3.4 KiB
C++
/* ----------------------------------------------------------------------------
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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 CameraResectioning.cpp
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* @brief An example of gtsam for solving the camera resectioning problem
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* @author Duy-Nguyen Ta
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* @date Aug 23, 2011
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*/
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#include <gtsam/inference/Symbol.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/geometry/SimpleCamera.h>
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#include <boost/make_shared.hpp>
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using namespace gtsam;
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using namespace gtsam::noiseModel;
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using symbol_shorthand::X;
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/**
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* Unary factor on the unknown pose, resulting from meauring the projection of
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* a known 3D point in the image
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*/
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class ResectioningFactor: public NoiseModelFactor1<Pose3> {
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typedef NoiseModelFactor1<Pose3> Base;
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Cal3_S2::shared_ptr K_; ///< camera's intrinsic parameters
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Point3 P_; ///< 3D point on the calibration rig
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Point2 p_; ///< 2D measurement of the 3D point
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public:
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/// Construct factor given known point P and its projection p
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ResectioningFactor(const SharedNoiseModel& model, const Key& key,
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const Cal3_S2::shared_ptr& calib, const Point2& p, const Point3& P) :
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Base(model, key), K_(calib), P_(P), p_(p) {
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}
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/// evaluate the error
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virtual Vector evaluateError(const Pose3& pose, boost::optional<Matrix&> H =
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boost::none) const {
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SimpleCamera camera(pose, *K_);
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Point2 reprojectionError(camera.project(P_, H) - p_);
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return reprojectionError.vector();
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}
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};
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/*******************************************************************************
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* Camera: f = 1, Image: 100x100, center: 50, 50.0
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* Pose (ground truth): (Xw, -Yw, -Zw, [0,0,2.0]')
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* Known landmarks:
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* 3D Points: (10,10,0) (-10,10,0) (-10,-10,0) (10,-10,0)
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* Perfect measurements:
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* 2D Point: (55,45) (45,45) (45,55) (55,55)
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*******************************************************************************/
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int main(int argc, char* argv[]) {
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/* read camera intrinsic parameters */
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Cal3_S2::shared_ptr calib(new Cal3_S2(1, 1, 0, 50, 50));
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/* 1. create graph */
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NonlinearFactorGraph graph;
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/* 2. add factors to the graph */
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// add measurement factors
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SharedDiagonal measurementNoise = Diagonal::Sigmas((Vec(2) << 0.5, 0.5));
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boost::shared_ptr<ResectioningFactor> factor;
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graph.push_back(
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boost::make_shared<ResectioningFactor>(measurementNoise, X(1), calib,
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Point2(55, 45), Point3(10, 10, 0)));
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graph.push_back(
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boost::make_shared<ResectioningFactor>(measurementNoise, X(1), calib,
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Point2(45, 45), Point3(-10, 10, 0)));
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graph.push_back(
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boost::make_shared<ResectioningFactor>(measurementNoise, X(1), calib,
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Point2(45, 55), Point3(-10, -10, 0)));
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graph.push_back(
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boost::make_shared<ResectioningFactor>(measurementNoise, X(1), calib,
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Point2(55, 55), Point3(10, -10, 0)));
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/* 3. Create an initial estimate for the camera pose */
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Values initial;
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initial.insert(X(1),
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Pose3(Rot3(1, 0, 0, 0, -1, 0, 0, 0, -1), Point3(0, 0, 2)));
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/* 4. Optimize the graph using Levenberg-Marquardt*/
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Values result = LevenbergMarquardtOptimizer(graph, initial).optimize();
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result.print("Final result:\n");
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return 0;
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}
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