401 lines
14 KiB
C++
401 lines
14 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 TestSmartProjectionFactor.cpp
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* @brief Unit tests for ProjectionFactor Class
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* @author Frank Dellaert
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* @date Nov 2009
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*/
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#include <CppUnitLite/TestHarness.h>
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#include <iostream>
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TEST(SmartProjectionFactor, disabled)
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{
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CHECK(("*** testSmartProjectionFactor is disabled *** - Needs conversion for unordered", 0));
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}
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#if 0
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#include <gtsam/slam/PriorFactor.h>
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#include <gtsam/slam/BetweenFactor.h>
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#include <gtsam/slam/ProjectionFactor.h>
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#include <gtsam_unstable/slam/SmartProjectionFactor.h>
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#include <gtsam/nonlinear/ISAM2.h>
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#include <gtsam/nonlinear/LevenbergMarquardtOptimizer.h>
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#include <gtsam/nonlinear/NonlinearFactorGraph.h>
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#include <gtsam/nonlinear/LinearContainerFactor.h>
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#include <gtsam/nonlinear/Values.h>
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#include <gtsam/nonlinear/Symbol.h>
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#include <gtsam/inference/JunctionTree.h>
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#include <gtsam_unstable/geometry/triangulation.h>
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#include <gtsam/geometry/Pose3.h>
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#include <gtsam/geometry/Point3.h>
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#include <gtsam/geometry/Point2.h>
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#include <gtsam/geometry/Cal3DS2.h>
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#include <gtsam/geometry/Cal3_S2.h>
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#include <gtsam/geometry/SimpleCamera.h>
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#include <boost/assign/std/vector.hpp>
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using namespace std;
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using namespace boost::assign;
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using namespace gtsam;
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// make a realistic calibration matrix
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static double fov = 60; // degrees
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static size_t w=640,h=480;
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static Cal3_S2::shared_ptr K(new Cal3_S2(fov,w,h));
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// Create a noise model for the pixel error
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static SharedNoiseModel model(noiseModel::Unit::Create(2));
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// Convenience for named keys
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using symbol_shorthand::X;
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using symbol_shorthand::L;
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typedef SmartProjectionFactor<Pose3, Point3> TestSmartProjectionFactor;
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/* ************************************************************************* */
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TEST( SmartProjectionFactor, Constructor) {
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Key poseKey(X(1));
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std::vector<Key> views;
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views += poseKey;
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std::vector<Point2> measurements;
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measurements.push_back(Point2(323.0, 240.0));
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TestSmartProjectionFactor factor(measurements, model, views, K);
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactor, ConstructorWithTransform) {
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Key poseKey(X(1));
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std::vector<Key> views;
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views += poseKey;
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std::vector<Point2> measurements;
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measurements.push_back(Point2(323.0, 240.0));
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Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
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TestSmartProjectionFactor factor(measurements, model, views, K, body_P_sensor);
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactor, Equals ) {
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// Create two identical factors and make sure they're equal
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std::vector<Point2> measurements;
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measurements.push_back(Point2(323.0, 240.0));
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std::vector<Key> views;
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views += X(1);
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TestSmartProjectionFactor factor1(measurements, model, views, K);
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TestSmartProjectionFactor factor2(measurements, model, views, K);
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CHECK(assert_equal(factor1, factor2));
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactor, EqualsWithTransform ) {
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// Create two identical factors and make sure they're equal
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std::vector<Point2> measurements;
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measurements.push_back(Point2(323.0, 240.0));
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Pose3 body_P_sensor(Rot3::RzRyRx(-M_PI_2, 0.0, -M_PI_2), Point3(0.25, -0.10, 1.0));
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std::vector<Key> views;
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views += X(1);
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TestSmartProjectionFactor factor1(measurements, model, views, K, body_P_sensor);
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TestSmartProjectionFactor factor2(measurements, model, views, K, body_P_sensor);
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CHECK(assert_equal(factor1, factor2));
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactor, noisy ){
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cout << " ************************ MultiProjectionFactor: noisy ****************************" << endl;
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Symbol x1('X', 1);
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Symbol x2('X', 2);
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const SharedDiagonal noiseProjection = noiseModel::Isotropic::Sigma(2, 1);
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std::vector<Key> views;
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views += x1, x2; //, x3;
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Cal3_S2::shared_ptr K(new Cal3_S2(1500, 1200, 0, 640, 480));
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// create first camera. Looking along X-axis, 1 meter above ground plane (x-y)
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Pose3 level_pose = Pose3(Rot3::ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1));
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SimpleCamera level_camera(level_pose, *K);
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// create second camera 1 meter to the right of first camera
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Pose3 level_pose_right = level_pose * Pose3(Rot3(), Point3(1,0,0));
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SimpleCamera level_camera_right(level_pose_right, *K);
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// landmark ~5 meters infront of camera
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Point3 landmark(5, 0.5, 1.2);
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// 1. Project two landmarks into two cameras and triangulate
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Point2 pixelError(0.2,0.2);
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Point2 level_uv = level_camera.project(landmark) + pixelError;
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Point2 level_uv_right = level_camera_right.project(landmark);
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Values values;
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values.insert(x1, level_pose);
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Pose3 noise_pose = Pose3(Rot3::ypr(-M_PI/10, 0., -M_PI/10), gtsam::Point3(0.5,0.1,0.3));
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values.insert(x2, level_pose_right.compose(noise_pose));
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vector<Point2> measurements;
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measurements += level_uv, level_uv_right;
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SmartProjectionFactor<Pose3, Point3, Cal3_S2>::shared_ptr
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smartFactor(new SmartProjectionFactor<Pose3, Point3, Cal3_S2>(measurements, noiseProjection, views, K));
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double actualError = smartFactor->error(values);
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std::cout << "Error: " << actualError << std::endl;
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// we do not expect to be able to predict the error, since the error on the pixel will change
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// the triangulation of the landmark which is internal to the factor.
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// DOUBLES_EQUAL(expectedError, actualError, 1e-7);
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactor, 3poses ){
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cout << " ************************ MultiProjectionFactor: 3 cams + 3 landmarks **********************" << endl;
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Symbol x1('X', 1);
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Symbol x2('X', 2);
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Symbol x3('X', 3);
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const SharedDiagonal noiseProjection = noiseModel::Isotropic::Sigma(2, 1);
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std::vector<Key> views;
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views += x1, x2, x3;
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Cal3_S2::shared_ptr K(new Cal3_S2(1500, 1200, 0, 640, 480));
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// create first camera. Looking along X-axis, 1 meter above ground plane (x-y)
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Pose3 pose1 = Pose3(Rot3::ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1));
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SimpleCamera cam1(pose1, *K);
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// create second camera 1 meter to the right of first camera
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Pose3 pose2 = pose1 * Pose3(Rot3(), Point3(1,0,0));
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SimpleCamera cam2(pose2, *K);
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// create third camera 1 meter above the first camera
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Pose3 pose3 = pose1 * Pose3(Rot3(), Point3(0,-1,0));
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SimpleCamera cam3(pose3, *K);
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// three landmarks ~5 meters infront of camera
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Point3 landmark1(5, 0.5, 1.2);
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Point3 landmark2(5, -0.5, 1.2);
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Point3 landmark3(3, 0, 3.0);
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vector<Point2> measurements_cam1, measurements_cam2, measurements_cam3;
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// 1. Project three landmarks into three cameras and triangulate
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Point2 cam1_uv1 = cam1.project(landmark1);
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Point2 cam2_uv1 = cam2.project(landmark1);
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Point2 cam3_uv1 = cam3.project(landmark1);
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measurements_cam1 += cam1_uv1, cam2_uv1, cam3_uv1;
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//
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Point2 cam1_uv2 = cam1.project(landmark2);
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Point2 cam2_uv2 = cam2.project(landmark2);
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Point2 cam3_uv2 = cam3.project(landmark2);
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measurements_cam2 += cam1_uv2, cam2_uv2, cam3_uv2;
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Point2 cam1_uv3 = cam1.project(landmark3);
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Point2 cam2_uv3 = cam2.project(landmark3);
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Point2 cam3_uv3 = cam3.project(landmark3);
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measurements_cam3 += cam1_uv3, cam2_uv3, cam3_uv3;
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typedef SmartProjectionFactor<Pose3, Point3, Cal3_S2> SmartFactor;
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SmartFactor::shared_ptr smartFactor1(new SmartFactor(measurements_cam1, noiseProjection, views, K));
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SmartFactor::shared_ptr smartFactor2(new SmartFactor(measurements_cam2, noiseProjection, views, K));
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SmartFactor::shared_ptr smartFactor3(new SmartFactor(measurements_cam3, noiseProjection, views, K));
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const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
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NonlinearFactorGraph graph;
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graph.push_back(smartFactor1);
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graph.push_back(smartFactor2);
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graph.push_back(smartFactor3);
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graph.push_back(PriorFactor<Pose3>(x1, pose1, noisePrior));
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graph.push_back(PriorFactor<Pose3>(x2, pose2, noisePrior));
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Pose3 noise_pose = Pose3(Rot3::ypr(-M_PI/100, 0., -M_PI/100), gtsam::Point3(0.1,0.1,0.1));
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Values values;
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values.insert(x1, pose1);
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values.insert(x2, pose2*noise_pose);
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values.insert(x3, pose3);
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LevenbergMarquardtParams params;
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params.verbosityLM = LevenbergMarquardtParams::TRYLAMBDA;
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params.verbosity = NonlinearOptimizerParams::ERROR;
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Values result;
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gttic_(SmartProjectionFactor);
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LevenbergMarquardtOptimizer optimizer(graph, values, params);
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result = optimizer.optimize();
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gttoc_(SmartProjectionFactor);
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tictoc_finishedIteration_();
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result.print("results of 3 camera, 3 landmark optimization \n");
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tictoc_print_();
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactor, 3poses_projection_factor ){
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cout << " ************************ Normal ProjectionFactor: 3 cams + 3 landmarks **********************" << endl;
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Symbol x1('X', 1);
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Symbol x2('X', 2);
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Symbol x3('X', 3);
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const SharedDiagonal noiseProjection = noiseModel::Isotropic::Sigma(2, 1);
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std::vector<Key> views;
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views += x1, x2, x3;
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Cal3_S2::shared_ptr K(new Cal3_S2(1500, 1200, 0, 640, 480));
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// create first camera. Looking along X-axis, 1 meter above ground plane (x-y)
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Pose3 pose1 = Pose3(Rot3::ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1));
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SimpleCamera cam1(pose1, *K);
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// create second camera 1 meter to the right of first camera
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Pose3 pose2 = pose1 * Pose3(Rot3(), Point3(1,0,0));
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SimpleCamera cam2(pose2, *K);
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// create third camera 1 meter above the first camera
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Pose3 pose3 = pose1 * Pose3(Rot3(), Point3(0,-1,0));
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pose3.print("Pose3: ");
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SimpleCamera cam3(pose3, *K);
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// three landmarks ~5 meters infront of camera
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Point3 landmark1(5, 0.5, 1.2);
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Point3 landmark2(5, -0.5, 1.2);
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Point3 landmark3(3, 0, 3.0);
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typedef GenericProjectionFactor<Pose3, Point3> ProjectionFactor;
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NonlinearFactorGraph graph;
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// 1. Project three landmarks into three cameras and triangulate
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graph.add(ProjectionFactor(cam1.project(landmark1), noiseProjection, x1, L(1), K));
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graph.add(ProjectionFactor(cam2.project(landmark1), noiseProjection, x2, L(1), K));
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graph.add(ProjectionFactor(cam3.project(landmark1), noiseProjection, x3, L(1), K));
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//
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graph.add(ProjectionFactor(cam1.project(landmark2), noiseProjection, x1, L(2), K));
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graph.add(ProjectionFactor(cam2.project(landmark2), noiseProjection, x2, L(2), K));
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graph.add(ProjectionFactor(cam3.project(landmark2), noiseProjection, x3, L(2), K));
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graph.add(ProjectionFactor(cam1.project(landmark3), noiseProjection, x1, L(3), K));
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graph.add(ProjectionFactor(cam2.project(landmark3), noiseProjection, x2, L(3), K));
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graph.add(ProjectionFactor(cam3.project(landmark3), noiseProjection, x3, L(3), K));
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const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
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graph.add(PriorFactor<Pose3>(x1, pose1, noisePrior));
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graph.add(PriorFactor<Pose3>(x2, pose2, noisePrior));
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Pose3 noise_pose = Pose3(Rot3::ypr(-M_PI/10, 0., -M_PI/10), gtsam::Point3(0.5,0.1,0.3));
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Values values;
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values.insert(x1, pose1);
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values.insert(x2, pose2);
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values.insert(x3, pose3* noise_pose);
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values.insert(L(1), landmark1);
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values.insert(L(2), landmark2);
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values.insert(L(3), landmark3);
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LevenbergMarquardtParams params;
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// params.verbosityLM = LevenbergMarquardtParams::TRYLAMBDA;
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// params.verbosity = NonlinearOptimizerParams::ERROR;
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LevenbergMarquardtOptimizer optimizer(graph, values, params);
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Values result = optimizer.optimize();
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result.print("Regular Projection Factor: results of 3 camera, 3 landmark optimization \n");
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}
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/* ************************************************************************* */
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TEST( SmartProjectionFactor, Hessian ){
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cout << " ************************ Normal ProjectionFactor: Hessian **********************" << endl;
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Symbol x1('X', 1);
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Symbol x2('X', 2);
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const SharedDiagonal noiseProjection = noiseModel::Isotropic::Sigma(2, 1);
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std::vector<Key> views;
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views += x1, x2;
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Cal3_S2::shared_ptr K(new Cal3_S2(1500, 1200, 0, 640, 480));
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// create first camera. Looking along X-axis, 1 meter above ground plane (x-y)
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Pose3 pose1 = Pose3(Rot3::ypr(-M_PI/2, 0., -M_PI/2), gtsam::Point3(0,0,1));
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SimpleCamera cam1(pose1, *K);
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// create second camera 1 meter to the right of first camera
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Pose3 pose2 = pose1 * Pose3(Rot3(), Point3(1,0,0));
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SimpleCamera cam2(pose2, *K);
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// three landmarks ~5 meters infront of camera
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Point3 landmark1(5, 0.5, 1.2);
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// 1. Project three landmarks into three cameras and triangulate
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Point2 cam1_uv1 = cam1.project(landmark1);
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Point2 cam2_uv1 = cam2.project(landmark1);
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vector<Point2> measurements_cam1;
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measurements_cam1 += cam1_uv1, cam2_uv1;
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SmartProjectionFactor<Pose3, Point3, Cal3_S2> smartFactor(measurements_cam1, noiseProjection, views, K);
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Pose3 noise_pose = Pose3(Rot3::ypr(-M_PI/10, 0., -M_PI/10), gtsam::Point3(0.5,0.1,0.3));
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Values values;
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values.insert(x1, pose1);
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values.insert(x2, pose2);
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// values.insert(L(1), landmark1);
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Ordering ordering;
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ordering.push_back(x1);
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ordering.push_back(x2);
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boost::shared_ptr<GaussianFactor> hessianFactor = smartFactor.linearize(values, ordering);
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hessianFactor->print("Hessian factor \n");
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// compute triangulation from linearization point
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// compute reprojection errors (sum squared)
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// compare with hessianFactor.info(): the bottom right element is the squared sum of the reprojection errors (normalized by the covariance)
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// check that it is correctly scaled when using noiseProjection = [1/4 0; 0 1/4]
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}
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#endif
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/* ************************************************************************* */
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int main() { TestResult tr; return TestRegistry::runAllTests(tr); }
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/* ************************************************************************* */
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