Extra constructor with calibration, unit tested
Frank Dellaert
parent
4f81d110f1
commit
fe3177c257
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@ -226,6 +226,19 @@ public:
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EssentialMatrixFactor2(key1, key2, pA, pB, model), cRb_(cRb) {
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}
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/**
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* Constructor
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* @param pA point in first camera, in pixel coordinates
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* @param pB point in second camera, in pixel coordinates
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* @param K calibration object, will be used only in constructor
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* @param model noise model should be in pixels, as well
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*/
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template<class CALIBRATION>
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EssentialMatrixFactor3(Key key1, Key key2, const Point2& pA, const Point2& pB,
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const Rot3& cRb, const SharedNoiseModel& model, boost::shared_ptr<CALIBRATION> K) :
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EssentialMatrixFactor2(key1, key2, pA, pB, model, K), cRb_(cRb) {
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}
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/// @return a deep copy of this factor
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virtual gtsam::NonlinearFactor::shared_ptr clone() const {
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return boost::static_pointer_cast<gtsam::NonlinearFactor>(
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@ -25,6 +25,10 @@ noiseModel::Isotropic::shared_ptr model1 = noiseModel::Isotropic::Sigma(1,
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// Noise model for second type of factor is evaluating pixel coordinates
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noiseModel::Unit::shared_ptr model2 = noiseModel::Unit::Create(2);
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// The rotation between body and camera is:
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gtsam::Point3 bX(1, 0, 0), bY(0, 1, 0), bZ(0, 0, 1);
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gtsam::Rot3 cRb = gtsam::Rot3(bX, bZ, -bY).inverse();
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namespace example1 {
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const string filename = findExampleDataFile("5pointExample1.txt");
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@ -32,6 +36,7 @@ SfM_data data;
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bool readOK = readBAL(filename, data);
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Rot3 c1Rc2 = data.cameras[1].pose().rotation();
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Point3 c1Tc2 = data.cameras[1].pose().translation();
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PinholeCamera<Cal3_S2> camera2(data.cameras[1].pose(),Cal3_S2());
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EssentialMatrix trueE(c1Rc2, c1Tc2);
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double baseline = 0.1; // actual baseline of the camera
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@ -149,8 +154,8 @@ TEST (EssentialMatrixFactor2, factor) {
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EssentialMatrixFactor2 factor(100, i, pA(i), pB(i), model2);
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// Check evaluation
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Point3 P1 = data.tracks[i].p, P2 = data.cameras[1].pose().transform_to(P1);
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const Point2 pi = SimpleCamera::project_to_camera(P2);
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Point3 P1 = data.tracks[i].p;
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const Point2 pi = camera2.project(P1);
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Point2 reprojectionError(pi - pB(i));
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Vector expected = reprojectionError.vector();
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@ -213,12 +218,8 @@ TEST (EssentialMatrixFactor2, minimization) {
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// body coordinate frame B which is rotated with respect to the camera
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// frame C, via the rotation bRc.
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// The rotation between body and camera is:
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gtsam::Point3 bX(1, 0, 0), bY(0, 1, 0), bZ(0, 0, 1);
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gtsam::Rot3 bRc(bX, bZ, -bY), cRb = bRc.inverse();
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// The "true E" in the body frame is then
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EssentialMatrix bodyE = bRc * trueE;
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EssentialMatrix bodyE = cRb.inverse() * trueE;
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//*************************************************************************
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TEST (EssentialMatrixFactor3, factor) {
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@ -227,8 +228,8 @@ TEST (EssentialMatrixFactor3, factor) {
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EssentialMatrixFactor3 factor(100, i, pA(i), pB(i), cRb, model2);
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// Check evaluation
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Point3 P1 = data.tracks[i].p, P2 = data.cameras[1].pose().transform_to(P1);
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const Point2 pi = SimpleCamera::project_to_camera(P2);
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Point3 P1 = data.tracks[i].p;
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const Point2 pi = camera2.project(P1);
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Point2 reprojectionError(pi - pB(i));
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Vector expected = reprojectionError.vector();
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@ -258,7 +259,16 @@ TEST (EssentialMatrixFactor3, minimization) {
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NonlinearFactorGraph graph;
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for (size_t i = 0; i < 5; i++)
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// but now we specify the rotation bRc
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graph.add(EssentialMatrixFactor3(100, i, pA(i), pB(i), bRc, model2));
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graph.add(EssentialMatrixFactor3(100, i, pA(i), pB(i), cRb, model2));
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// Check error at ground truth
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Values truth;
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truth.insert(100, bodyE);
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for (size_t i = 0; i < 5; i++) {
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Point3 P1 = data.tracks[i].p;
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truth.insert(i, LieScalar(baseline / P1.z()));
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}
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EXPECT_DOUBLES_EQUAL(0, graph.error(truth), 1e-8);
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}
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} // namespace example1
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@ -272,6 +282,8 @@ SfM_data data;
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bool readOK = readBAL(filename, data);
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Rot3 aRb = data.cameras[1].pose().rotation();
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Point3 aTb = data.cameras[1].pose().translation();
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EssentialMatrix trueE(aRb, aTb);
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double baseline = 10; // actual baseline of the camera
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Point2 pA(size_t i) {
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@ -283,6 +295,7 @@ Point2 pB(size_t i) {
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boost::shared_ptr<Cal3Bundler> //
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K = boost::make_shared<Cal3Bundler>(500, 0, 0);
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PinholeCamera<Cal3Bundler> camera2(data.cameras[1].pose(),*K);
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Vector vA(size_t i) {
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Point2 xy = K->calibrate(pA(i));
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@ -294,7 +307,7 @@ Vector vB(size_t i) {
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}
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//*************************************************************************
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TEST (EssentialMatrixFactor, extraTest) {
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TEST (EssentialMatrixFactor, extraMinimization) {
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// Additional test with camera moving in positive X direction
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NonlinearFactorGraph graph;
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@ -303,7 +316,6 @@ TEST (EssentialMatrixFactor, extraTest) {
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// Check error at ground truth
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Values truth;
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EssentialMatrix trueE(aRb, aTb);
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truth.insert(1, trueE);
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EXPECT_DOUBLES_EQUAL(0, graph.error(truth), 1e-8);
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@ -334,6 +346,36 @@ TEST (EssentialMatrixFactor, extraTest) {
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//*************************************************************************
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TEST (EssentialMatrixFactor2, extraTest) {
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for (size_t i = 0; i < 5; i++) {
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EssentialMatrixFactor2 factor(100, i, pA(i), pB(i), model2, K);
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// Check evaluation
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Point3 P1 = data.tracks[i].p;
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const Point2 pi = camera2.project(P1);
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Point2 reprojectionError(pi - pB(i));
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Vector expected = reprojectionError.vector();
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Matrix Hactual1, Hactual2;
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LieScalar d(baseline / P1.z());
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Vector actual = factor.evaluateError(trueE, d, Hactual1, Hactual2);
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EXPECT(assert_equal(expected, actual, 1e-7));
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// Use numerical derivatives to calculate the expected Jacobian
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Matrix Hexpected1, Hexpected2;
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boost::function<Vector(const EssentialMatrix&, const LieScalar&)> f =
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boost::bind(&EssentialMatrixFactor2::evaluateError, &factor, _1, _2,
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boost::none, boost::none);
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Hexpected1 = numericalDerivative21<EssentialMatrix>(f, trueE, d);
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Hexpected2 = numericalDerivative22<EssentialMatrix>(f, trueE, d);
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// Verify the Jacobian is correct
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EXPECT(assert_equal(Hexpected1, Hactual1, 1e-6));
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EXPECT(assert_equal(Hexpected2, Hactual2, 1e-8));
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}
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}
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//*************************************************************************
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TEST (EssentialMatrixFactor2, extraMinimization) {
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// Additional test with camera moving in positive X direction
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// We start with a factor graph and add constraints to it
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@ -344,7 +386,6 @@ TEST (EssentialMatrixFactor2, extraTest) {
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// Check error at ground truth
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Values truth;
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EssentialMatrix trueE(aRb, aTb);
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truth.insert(100, trueE);
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for (size_t i = 0; i < data.number_tracks(); i++) {
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Point3 P1 = data.tracks[i].p;
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@ -368,6 +409,40 @@ TEST (EssentialMatrixFactor2, extraTest) {
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EXPECT_DOUBLES_EQUAL(0, graph.error(result), 1e-4);
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}
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//*************************************************************************
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TEST (EssentialMatrixFactor3, extraTest) {
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// The "true E" in the body frame is
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EssentialMatrix bodyE = cRb.inverse() * trueE;
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for (size_t i = 0; i < 5; i++) {
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EssentialMatrixFactor3 factor(100, i, pA(i), pB(i), cRb, model2, K);
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// Check evaluation
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Point3 P1 = data.tracks[i].p;
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const Point2 pi = camera2.project(P1);
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Point2 reprojectionError(pi - pB(i));
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Vector expected = reprojectionError.vector();
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Matrix Hactual1, Hactual2;
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LieScalar d(baseline / P1.z());
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Vector actual = factor.evaluateError(bodyE, d, Hactual1, Hactual2);
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EXPECT(assert_equal(expected, actual, 1e-7));
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// Use numerical derivatives to calculate the expected Jacobian
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Matrix Hexpected1, Hexpected2;
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boost::function<Vector(const EssentialMatrix&, const LieScalar&)> f =
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boost::bind(&EssentialMatrixFactor3::evaluateError, &factor, _1, _2,
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boost::none, boost::none);
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Hexpected1 = numericalDerivative21<EssentialMatrix>(f, bodyE, d);
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Hexpected2 = numericalDerivative22<EssentialMatrix>(f, bodyE, d);
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// Verify the Jacobian is correct
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EXPECT(assert_equal(Hexpected1, Hactual1, 1e-6));
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EXPECT(assert_equal(Hexpected2, Hactual2, 1e-8));
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}
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}
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} // namespace example2
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/* ************************************************************************* */
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