SmartProjectionFactor: More cleanup, added more tests, added some timing
Zsolt Kira
parent
d33f435eab
commit
f423d6f2a8
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@ -146,7 +146,8 @@ namespace gtsam {
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/// linearize returns a Hessianfactor that is an approximation of error(p)
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virtual boost::shared_ptr<GaussianFactor> linearize(const Values& values, const Ordering& ordering) const {
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bool debug = true;
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bool debug = false;
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bool blockwise = true;
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// Collect all poses (Cameras)
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std::vector<Pose3> cameraPoses;
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@ -177,7 +178,6 @@ namespace gtsam {
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js += ordering[k];
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}
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bool blockwise = false;
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// For debug only
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std::vector<Matrix> Gs1;
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std::vector<Vector> gs1;
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@ -212,8 +212,7 @@ namespace gtsam {
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for(size_t i2 = 0; i2 < keys_.size(); i2++) {
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// we only need the upper triangular entries
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Hxl[i1][i2] = Hx.at(i1).transpose() * Hl.at(i1) * C * Hl.at(i2).transpose();
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if (i1==0 & i2==0){
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if (i1==0 && i2==0){
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if (debug) {
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std::cout << "Hoff"<< i1 << i2 << "=[" << Hx.at(i1).transpose() * Hl.at(i1) * C * Hl.at(i2).transpose() << "];" << std::endl;
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std::cout << "Hxoff"<< "=[" << Hx.at(i1) << "];" << std::endl;
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@ -373,17 +372,12 @@ namespace gtsam {
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if(point)
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{ // triangulation produced a good estimate of landmark position
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// std::cout << "point " << *point << std::endl;
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for(size_t i = 0; i < measured_.size(); i++) {
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Pose3 pose = cameraPoses.at(i);
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PinholeCamera<CALIBRATION> camera(pose, *K_);
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// std::cout << "pose.compose(*body_P_sensor_) " << pose << std::endl;
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Point2 reprojectionError(camera.project(*point) - measured_.at(i));
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// std::cout << "reprojectionError " << reprojectionError << std::endl;
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overallError += noise_->distance( reprojectionError.vector() );
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// std::cout << "noise_->distance( reprojectionError.vector() ) " << noise_->distance( reprojectionError.vector() ) << std::endl;
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}
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return sqrt(overallError);
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}else{ // triangulation failed: we deactivate the factor, then the error should not contribute to the overall error
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@ -10,7 +10,7 @@
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* -------------------------------------------------------------------------- */
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/**
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* @file testProjectionFactor.cpp
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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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@ -56,63 +56,71 @@ static SharedNoiseModel model(noiseModel::Unit::Create(2));
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using symbol_shorthand::X;
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using symbol_shorthand::L;
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//typedef GenericProjectionFactor<Pose3, Point3> TestProjectionFactor;
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typedef SmartProjectionFactor<Pose3, Point3> TestSmartProjectionFactor;
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/* ************************************************************************* *
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TEST( MultiProjectionFactor, noiseless ){
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cout << " ************************ MultiProjectionFactor: noiseless ****************************" << endl;
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Values theta;
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NonlinearFactorGraph graph;
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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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/* ************************************************************************* */
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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 += x1, x2; //, x3;
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views += poseKey;
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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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std::vector<Point2> measurements;
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measurements.push_back(Point2(323.0, 240.0));
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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 level_uv = level_camera.project(landmark);
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Point2 level_uv_right = level_camera_right.project(landmark);
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Values value;
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value.insert(x1, level_pose);
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value.insert(x2, level_pose_right);
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// poses += level_pose, level_pose_right;
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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> smartFactor(measurements, noiseProjection, views, K);
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double actualError = smartFactor.error(value);
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double expectedError = 0.0;
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DOUBLES_EQUAL(expectedError, actualError, 1e-7);
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TestSmartProjectionFactor factor(measurements, model, views, K);
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}
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/* ************************************************************************* *
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TEST( MultiProjectionFactor, noisy ){
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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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// Symbol x3('X', 3);
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const SharedDiagonal noiseProjection = noiseModel::Isotropic::Sigma(2, 1);
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@ -120,6 +128,7 @@ TEST( MultiProjectionFactor, noisy ){
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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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@ -141,7 +150,6 @@ TEST( MultiProjectionFactor, noisy ){
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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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// poses += level_pose, level_pose_right;
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vector<Point2> measurements;
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measurements += level_uv, level_uv_right;
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@ -149,16 +157,16 @@ TEST( MultiProjectionFactor, noisy ){
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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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double expectedError = sqrt(0.08);
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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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// DOUBLES_EQUAL(expectedError, actualError, 1e-7);
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}
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/* ************************************************************************* */
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TEST( MultiProjectionFactor, 3poses ){
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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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@ -171,6 +179,7 @@ TEST( MultiProjectionFactor, 3poses ){
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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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@ -214,9 +223,6 @@ TEST( MultiProjectionFactor, 3poses ){
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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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// double actualError = smartFactor->error(values);
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// double expectedError = sqrt(0.08);
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const SharedDiagonal noisePrior = noiseModel::Isotropic::Sigma(6, 0.10);
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NonlinearFactorGraph graph;
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@ -226,9 +232,6 @@ TEST( MultiProjectionFactor, 3poses ){
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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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// smartFactor1->print("smartFactor1");
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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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@ -238,16 +241,23 @@ TEST( MultiProjectionFactor, 3poses ){
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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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Values result = optimizer.optimize();
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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( MultiProjectionFactor, 3poses_projection_factor ){
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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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