Examples with DMatrixRMaj org.ejml.data.DMatrixRMaj used on opensource projects

Example 26 with DMatrixRMaj

use of org.ejml.data.DMatrixRMaj in project BoofCV by lessthanoptimal.

the class TestTrifocalAlgebraicPoint7 method checkInducedErrors.

/**
 * Computes the error using induced homographies.
 */
public void checkInducedErrors(TrifocalTensor tensor, List<AssociatedTriple> observations, double tol) {
    for (AssociatedTriple o : observations) {
        // homogeneous vector for observations in views 2 and 3
        Vector3D_F64 obs2 = new Vector3D_F64(o.p2.x, o.p2.y, 1);
        Vector3D_F64 obs3 = new Vector3D_F64(o.p3.x, o.p3.y, 1);
        // compute lines which pass through the observations
        Vector3D_F64 axisY = new Vector3D_F64(0, 1, 0);
        Vector3D_F64 line2 = new Vector3D_F64();
        Vector3D_F64 line3 = new Vector3D_F64();
        GeometryMath_F64.cross(obs2, axisY, line2);
        GeometryMath_F64.cross(obs3, axisY, line3);
        // compute induced homographies
        DMatrixRMaj H12 = MultiViewOps.inducedHomography12(tensor, line3, null);
        DMatrixRMaj H13 = MultiViewOps.inducedHomography13(tensor, line2, null);
        Point2D_F64 induced2 = new Point2D_F64();
        Point2D_F64 induced3 = new Point2D_F64();
        GeometryMath_F64.mult(H12, o.p1, induced2);
        GeometryMath_F64.mult(H13, o.p1, induced3);
        assertEquals(0, induced2.distance(o.p2), tol);
        assertEquals(0, induced3.distance(o.p3), tol);
    }
}

Example 27 with DMatrixRMaj

use of org.ejml.data.DMatrixRMaj in project BoofCV by lessthanoptimal.

the class TestTrifocalLinearPoint7 method fullTest.

@Test
public void fullTest() {
    TrifocalLinearPoint7 alg = new TrifocalLinearPoint7();
    assertTrue(alg.process(observations, found));
    // validate the solution by using a constraint
    for (AssociatedTriple a : observations) {
        DMatrixRMaj A = MultiViewOps.constraint(found, a.p1, a.p2, a.p3, null);
        assertEquals(0, NormOps_DDRM.normF(A), 1e-7);
    }
}

Example 28 with DMatrixRMaj

use of org.ejml.data.DMatrixRMaj in project BoofCV by lessthanoptimal.

the class TestBaseDetectFiducialSquare method render.

/**
 * Draws a distorted pattern onto the output
 */
public static void render(GrayU8 pattern, Quadrilateral_F64 where, GrayU8 output) {
    int w = pattern.width;
    int h = pattern.height;
    ArrayList<AssociatedPair> associatedPairs = new ArrayList<>();
    associatedPairs.add(new AssociatedPair(where.a, new Point2D_F64(0, 0)));
    associatedPairs.add(new AssociatedPair(where.b, new Point2D_F64(w, 0)));
    associatedPairs.add(new AssociatedPair(where.c, new Point2D_F64(w, h)));
    associatedPairs.add(new AssociatedPair(where.d, new Point2D_F64(0, h)));
    Estimate1ofEpipolar computeHomography = FactoryMultiView.computeHomographyDLT(true);
    DMatrixRMaj H = new DMatrixRMaj(3, 3);
    computeHomography.process(associatedPairs, H);
    // Create the transform for distorting the image
    FMatrixRMaj H32 = new FMatrixRMaj(3, 3);
    ConvertMatrixData.convert(H, H32);
    PointTransformHomography_F32 homography = new PointTransformHomography_F32(H32);
    PixelTransform2_F32 pixelTransform = new PointToPixelTransform_F32(homography);
    // Apply distortion and show the results
    DistortImageOps.distortSingle(pattern, output, pixelTransform, InterpolationType.BILINEAR, BorderType.SKIP);
// ShowImages.showWindow(output, "Rendered");
// try {Thread.sleep(10000);} catch (InterruptedException e) {}
}

Example 29 with DMatrixRMaj

use of org.ejml.data.DMatrixRMaj in project BoofCV by lessthanoptimal.

the class ImplPerspectiveOps_F64 method calibrationMatrix.

public static DMatrixRMaj calibrationMatrix(CameraPinhole param, DMatrixRMaj K) {
    if (K == null) {
        K = new DMatrixRMaj(3, 3);
    }
    CommonOps_DDRM.fill(K, 0);
    K.data[0] = (double) param.fx;
    K.data[1] = (double) param.skew;
    K.data[2] = (double) param.cx;
    K.data[4] = (double) param.fy;
    K.data[5] = (double) param.cy;
    K.data[8] = 1;
    return K;
}

Example 30 with DMatrixRMaj

use of org.ejml.data.DMatrixRMaj in project BoofCV by lessthanoptimal.

the class PnPLepetitEPnP method selectWorldControlPoints.

/**
 * Selects control points along the data's axis and the data's centroid.  If the data is determined
 * to be planar then only 3 control points are selected.
 *
 * The data's axis is determined by computing the covariance matrix then performing SVD.  The axis
 * is contained along the
 */
public void selectWorldControlPoints(List<Point3D_F64> worldPts, FastQueue<Point3D_F64> controlWorldPts) {
    UtilPoint3D_F64.mean(worldPts, meanWorldPts);
    // covariance matrix elements, summed up here for speed
    double c11 = 0, c12 = 0, c13 = 0, c22 = 0, c23 = 0, c33 = 0;
    final int N = worldPts.size();
    for (int i = 0; i < N; i++) {
        Point3D_F64 p = worldPts.get(i);
        double dx = p.x - meanWorldPts.x;
        double dy = p.y - meanWorldPts.y;
        double dz = p.z - meanWorldPts.z;
        c11 += dx * dx;
        c12 += dx * dy;
        c13 += dx * dz;
        c22 += dy * dy;
        c23 += dy * dz;
        c33 += dz * dz;
    }
    c11 /= N;
    c12 /= N;
    c13 /= N;
    c22 /= N;
    c23 /= N;
    c33 /= N;
    DMatrixRMaj covar = new DMatrixRMaj(3, 3, true, c11, c12, c13, c12, c22, c23, c13, c23, c33);
    // find the data's orientation and check to see if it is planar
    svd.decompose(covar);
    double[] singularValues = svd.getSingularValues();
    DMatrixRMaj V = svd.getV(null, false);
    SingularOps_DDRM.descendingOrder(null, false, singularValues, 3, V, false);
    // planar check
    if (singularValues[0] < singularValues[2] * 1e13) {
        numControl = 4;
    } else {
        numControl = 3;
    }
    // put control points along the data's major axises
    controlWorldPts.reset();
    for (int i = 0; i < numControl - 1; i++) {
        double m = Math.sqrt(singularValues[1]) * magicNumber;
        double vx = V.unsafe_get(0, i) * m;
        double vy = V.unsafe_get(1, i) * m;
        double vz = V.unsafe_get(2, i) * m;
        controlWorldPts.grow().set(meanWorldPts.x + vx, meanWorldPts.y + vy, meanWorldPts.z + vz);
    }
    // set a control point to be the centroid
    controlWorldPts.grow().set(meanWorldPts.x, meanWorldPts.y, meanWorldPts.z);
}