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Checked evaluation and calculation

release/4.3a0
Frank Dellaert 2013-12-23 22:29:09 -05:00
parent ce7cf524ea
commit 92c1398cd2
1 changed files with 57 additions and 22 deletions
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79
gtsam/slam/tests/testEssentialMatrixFactor.cpp
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@ -6,27 +6,30 @@
*/
#include <gtsam/slam/EssentialMatrixFactor.h>
#include <gtsam/geometry/SimpleCamera.h>
#include <gtsam/base/LieScalar.h>
namespace gtsam {
/**
* Binary factor that optimizes for E and inverse depth: assumes measurement
* in image 1 is perfect, and returns re-projection error in image 2
* in image 2 is perfect, and returns re-projection error in image 1
*/
class EssentialMatrixFactor2: public NoiseModelFactor2<EssentialMatrix,
LieScalar> {
Point2 pA_, pB_; ///< Measurements in image A and B
Cal3_S2 K_; ///< Calibration
typedef NoiseModelFactor2<EssentialMatrix, LieScalar> Base;
typedef EssentialMatrixFactor2 This;
public:
/// Constructor
EssentialMatrixFactor2(Key key1, Key key2, const Point2& pA, const Point2& pB,
const SharedNoiseModel& model) :
Base(model, key1, key2), pA_(pA), pB_(pB) {
const Cal3_S2& K, const SharedNoiseModel& model) :
Base(model, key1, key2), pA_(pA), pB_(pB), K_(K) {
}
/// print
@ -42,16 +45,32 @@ public:
Vector evaluateError(const EssentialMatrix& E, const LieScalar& d,
boost::optional<Matrix&> H1 = boost::none, boost::optional<Matrix&> H2 =
boost::none) const {
// We have point x,y in image 1
// Given a depth Z, the corresponding 3D point P1 = Z*(x,y,1) = (x,y,1)/d
// We then convert to first camera by 2P = 1R2Õ*(P1-1T2)
// The homogeneous coordinates of can be written as
// 2R1*(P1-1T2) == 2R1*d*(P1-1T2) == 2R1*((x,y,1)-d*1T2)
// Note that this is just a homography for d==0
Point3 dP1(pA_.x(), pA_.y(), 1);
Point3 P2 = E.rotation().unrotate(dP1 - d * E.direction().point3());
// Project to normalized image coordinates, then uncalibrate
const Point2 pn = SimpleCamera::project_to_camera(P2);
const Point2 pi = K_.uncalibrate(pn);
Point2 reprojectionError(pi - pB_);
if (H1)
*H1 = zeros(2, 5);
if (H2)
*H2 = zeros(2, 1);
return (Vector(2) << 0,0);
return reprojectionError.vector();
}
};
} // gtsam
}
// gtsam
#include <gtsam/slam/dataset.h>
#include <gtsam/nonlinear/NonlinearFactorGraph.h>
@ -187,31 +206,47 @@ TEST (EssentialMatrixFactor, fromConstraints) {
//*************************************************************************
TEST (EssentialMatrixFactor2, factor) {
EssentialMatrix trueE(aRb, aTb);
LieScalar d(5);
EssentialMatrix E(aRb, aTb);
noiseModel::Unit::shared_ptr model = noiseModel::Unit::Create(1);
for (size_t i = 0; i < 5; i++) {
EssentialMatrixFactor2 factor(100, i, pA(i), pB(i), model);
Cal3_S2 K;
EssentialMatrixFactor2 factor(100, i, pA(i), pB(i), K, model);
// Check evaluation
Vector expected(1);
expected << 0;
Point3 P1 = data.tracks[i].p, P2 = E.transform_to(P1);
LieScalar d(1.0 / P1.z());
const Point2 pn = SimpleCamera::project_to_camera(P2);
const Point2 pi = K.uncalibrate(pn);
Point2 reprojectionError(pi - pB(i));
Vector expected = reprojectionError.vector();
{
// Check calculations
Point3 dP1(pA(i).x(), pA(i).y(), 1);
EXPECT_DOUBLES_EQUAL(pA(i).x(), P1.x()/P1.z(), 1e-8);
EXPECT_DOUBLES_EQUAL(pA(i).y(), P1.y()/P1.z(), 1e-8);
EXPECT(assert_equal(P1,dP1/d));
Point3 otherP2 = E.rotation().unrotate(
d * P1 - d * E.direction().point3());
EXPECT(assert_equal(P2,otherP2/d));
}
Matrix Hactual1, Hactual2;
Vector actual = factor.evaluateError(trueE, d, Hactual1, Hactual2);
Vector actual = factor.evaluateError(E, d, Hactual1, Hactual2);
EXPECT(assert_equal(expected, actual, 1e-7));
// Use numerical derivatives to calculate the expected Jacobian
Matrix Hexpected1, Hexpected2;
boost::function<Vector(const EssentialMatrix&, const LieScalar&)> f =
boost::bind(&EssentialMatrixFactor2::evaluateError, &factor, _1, _2,
boost::none, boost::none);
Hexpected1 = numericalDerivative21<EssentialMatrix>(f, trueE, d);
Hexpected2 = numericalDerivative22<EssentialMatrix>(f, trueE, d);
// Verify the Jacobian is correct
EXPECT(assert_equal(Hexpected1, Hactual1, 1e-8));
EXPECT(assert_equal(Hexpected2, Hactual2, 1e-8));
// // Use numerical derivatives to calculate the expected Jacobian
// Matrix Hexpected1, Hexpected2;
// boost::function<Vector(const EssentialMatrix&, const LieScalar&)> f =
// boost::bind(&EssentialMatrixFactor2::evaluateError, &factor, _1, _2,
// boost::none, boost::none);
// Hexpected1 = numericalDerivative21<EssentialMatrix>(f, E, d);
// Hexpected2 = numericalDerivative22<EssentialMatrix>(f, E, d);
//
// // Verify the Jacobian is correct
// EXPECT(assert_equal(Hexpected1, Hactual1, 1e-8));
// EXPECT(assert_equal(Hexpected2, Hactual2, 1e-8));
}
}