Examples with Ransac org.ddogleg.fitting.modelset.ransac.Ransac used on opensource projects

Example 6 with Ransac

use of org.ddogleg.fitting.modelset.ransac.Ransac in project BoofCV by lessthanoptimal.

the class FactoryMultiViewRobust method epipolarRansac.

private static Ransac<Se3_F64, AssociatedPair> epipolarRansac(Estimate1ofEpipolar epipolar, CameraPinholeRadial intrinsic, ConfigRansac ransac) {
    TriangulateTwoViewsCalibrated triangulate = FactoryMultiView.triangulateTwoGeometric();
    ModelManager<Se3_F64> manager = new ModelManagerSe3_F64();
    ModelGenerator<Se3_F64, AssociatedPair> generateEpipolarMotion = new Se3FromEssentialGenerator(epipolar, triangulate);
    DistanceFromModel<Se3_F64, AssociatedPair> distanceSe3 = new DistanceSe3SymmetricSq(triangulate, intrinsic.fx, intrinsic.fy, intrinsic.skew, intrinsic.fx, intrinsic.fy, intrinsic.skew);
    double ransacTOL = ransac.inlierThreshold * ransac.inlierThreshold * 2.0;
    return new Ransac<>(ransac.randSeed, manager, generateEpipolarMotion, distanceSe3, ransac.maxIterations, ransacTOL);
}

Example 7 with Ransac

use of org.ddogleg.fitting.modelset.ransac.Ransac in project MAVSlam by ecmnet.

the class FactoryMAVOdometry method depthDepthPnP.

/**
 * Depth sensor based visual odometry algorithm which runs a sparse feature tracker in the visual camera and
 * estimates the range of tracks once when first detected using the depth sensor.
 *
 * @see MAVOdomPixelDepthPnP
 *
 * @param thresholdAdd Add new tracks when less than this number are in the inlier set.  Tracker dependent. Set to
 *                     a value ≤ 0 to add features every frame.
 * @param thresholdRetire Discard a track if it is not in the inlier set after this many updates.  Try 2
 * @param sparseDepth Extracts depth of pixels from a depth sensor.
 * @param visualType Type of visual image being processed.
 * @param depthType Type of depth image being processed.
 * @return StereoVisualOdometry
 */
public static <Vis extends ImageGray, Depth extends ImageGray> MAVDepthVisualOdometry<Vis, Depth> depthDepthPnP(double inlierPixelTol, int thresholdAdd, int thresholdRetire, int ransacIterations, int refineIterations, boolean doublePass, DepthSparse3D<Depth> sparseDepth, PointTrackerTwoPass<Vis> tracker, Class<Vis> visualType, Class<Depth> depthType) {
    // Range from sparse disparity
    ImagePixelTo3D pixelTo3D = new DepthSparse3D_to_PixelTo3D<Depth>(sparseDepth);
    Estimate1ofPnP estimator = FactoryMultiView.computePnP_1(EnumPNP.P3P_FINSTERWALDER, -1, 2);
    final DistanceModelMonoPixels<Se3_F64, Point2D3D> distance = new PnPDistanceReprojectionSq();
    ModelManagerSe3_F64 manager = new ModelManagerSe3_F64();
    EstimatorToGenerator<Se3_F64, Point2D3D> generator = new EstimatorToGenerator<Se3_F64, Point2D3D>(estimator);
    // 1/2 a pixel tolerance for RANSAC inliers
    double ransacTOL = inlierPixelTol * inlierPixelTol;
    ModelMatcher<Se3_F64, Point2D3D> motion = new Ransac<Se3_F64, Point2D3D>(2323, manager, generator, distance, ransacIterations, ransacTOL);
    RefinePnP refine = null;
    if (refineIterations > 0) {
        refine = FactoryMultiView.refinePnP(1e-12, refineIterations);
    }
    MAVOdomPixelDepthPnP<Vis> alg = new MAVOdomPixelDepthPnP<Vis>(thresholdAdd, thresholdRetire, doublePass, motion, pixelTo3D, refine, tracker, null, null);
    return new MAVOdomPixelDepthPnP_to_DepthVisualOdometry<Vis, Depth>(sparseDepth, alg, distance, ImageType.single(visualType), depthType);
}

Example 8 with Ransac

use of org.ddogleg.fitting.modelset.ransac.Ransac in project BoofCV by lessthanoptimal.

the class FactoryMultiViewRobust method pnpRansac.

/**
 * Robust solution to PnP problem using {@link Ransac}.  Input observations are in normalized
 * image coordinates.
 *
 * <p>NOTE: Observations are in normalized image coordinates NOT pixels.</p>
 *
 * <p>See code for all the details.</p>
 *
 * @param pnp PnP parameters.  Can't be null.
 * @param ransac Parameters for RANSAC.  Can't be null.
 * @return Robust Se3_F64 estimator
 */
public static Ransac<Se3_F64, Point2D3D> pnpRansac(ConfigPnP pnp, ConfigRansac ransac) {
    pnp.checkValidity();
    ransac.checkValidity();
    Estimate1ofPnP estimatorPnP = FactoryMultiView.computePnP_1(pnp.which, pnp.epnpIterations, pnp.numResolve);
    DistanceModelMonoPixels<Se3_F64, Point2D3D> distance = new PnPDistanceReprojectionSq();
    distance.setIntrinsic(pnp.intrinsic.fx, pnp.intrinsic.fy, pnp.intrinsic.skew);
    ModelManagerSe3_F64 manager = new ModelManagerSe3_F64();
    EstimatorToGenerator<Se3_F64, Point2D3D> generator = new EstimatorToGenerator<>(estimatorPnP);
    // convert from pixels to pixels squared
    double threshold = ransac.inlierThreshold * ransac.inlierThreshold;
    return new Ransac<>(ransac.randSeed, manager, generator, distance, ransac.maxIterations, threshold);
}

Example 9 with Ransac

use of org.ddogleg.fitting.modelset.ransac.Ransac in project BoofCV by lessthanoptimal.

the class FactoryMultiViewRobust method homographyRansac.

/**
 * Robust solution for estimating {@link Homography2D_F64} with {@link Ransac}.  Input
 * observations are in pixel coordinates.
 *
 * <ul>
 *     <li>Four point linear is used internally</p>
 *     <li>inlierThreshold is in pixels</p>
 * </ul>
 *
 * <p>See code for all the details.</p>
 *
 * @param homography Homography estimation parameters.  If null default is used.
 * @param ransac Parameters for RANSAC.  Can't be null.
 * @return Homography estimator
 */
public static Ransac<Homography2D_F64, AssociatedPair> homographyRansac(ConfigHomography homography, ConfigRansac ransac) {
    if (homography == null)
        homography = new ConfigHomography();
    ModelManager<Homography2D_F64> manager = new ModelManagerHomography2D_F64();
    GenerateHomographyLinear modelFitter = new GenerateHomographyLinear(homography.normalize);
    DistanceHomographySq distance = new DistanceHomographySq();
    double ransacTol = ransac.inlierThreshold * ransac.inlierThreshold;
    return new Ransac<>(ransac.randSeed, manager, modelFitter, distance, ransac.maxIterations, ransacTol);
}

Example 10 with Ransac

use of org.ddogleg.fitting.modelset.ransac.Ransac in project BoofCV by lessthanoptimal.

the class CommonGridRansacLineDetectorChecks method checkObvious.

/**
 * Give it a single straight line and see if it can detect it.  Allow the region size to be changed to check
 * for issues related to that
 * @param regionSize
 */
protected void checkObvious(int regionSize) {
    // System.out.println("regionSize = "+regionSize);
    int where = 25;
    GrayU8 edgeImage = new GrayU8(width, height);
    D derivX = GeneralizedImageOps.createSingleBand(derivType, width, height);
    D derivY = GeneralizedImageOps.createSingleBand(derivType, width, height);
    for (int i = 0; i < height; i++) {
        edgeImage.set(where, i, 1);
        GeneralizedImageOps.set(derivX, where, i, 20);
    }
    ModelManagerLinePolar2D_F32 manager = new ModelManagerLinePolar2D_F32();
    GridLineModelDistance distance = new GridLineModelDistance(0.9f);
    GridLineModelFitter fitter = new GridLineModelFitter(0.9f);
    ModelMatcher<LinePolar2D_F32, Edgel> matcher = new Ransac<>(123123, manager, fitter, distance, 25, 1);
    GridRansacLineDetector<D> alg = createDetector(regionSize, 5, matcher);
    alg.process(derivX, derivY, edgeImage);
    MatrixOfList<LineSegment2D_F32> lines = alg.getFoundLines();
    assertEquals(width / regionSize, lines.getWidth());
    assertEquals(height / regionSize, lines.getHeight());
    int gridCol = where / regionSize;
    for (int i = 0; i < lines.height; i++) {
        List<LineSegment2D_F32> l = lines.get(gridCol, i);
        assertTrue(l.size() == 1);
        LineSegment2D_F32 a = l.get(0);
        assertTrue(Math.abs(a.slopeY()) > 1);
        assertTrue(Math.abs(a.slopeX()) < 0.01);
    }
}