Examples with ModelManagerHomography2D_F64 georegression.fitting.homography.ModelManagerHomography2D_F64 used on opensource projects

Example 1 with ModelManagerHomography2D_F64

use of georegression.fitting.homography.ModelManagerHomography2D_F64 in project BoofCV by lessthanoptimal.

the class FactoryMotion2D method createMotion2D.

/**
 * Estimates the 2D motion of an image using different models.
 *
 * @param ransacIterations Number of RANSAC iterations
 * @param inlierThreshold Threshold which defines an inlier.
 * @param outlierPrune If a feature is an outlier for this many turns in a row it is dropped. Try 2
 * @param absoluteMinimumTracks New features will be respawned if the number of inliers drop below this number.
 * @param respawnTrackFraction If the fraction of current inliers to the original number of inliers drops below
 *                             this fraction then new features are spawned.  Try 0.3
 * @param respawnCoverageFraction If the area covered drops by this fraction then spawn more features.  Try 0.8
 * @param refineEstimate Should it refine the model estimate using all inliers.
 * @param tracker Point feature tracker.
 * @param motionModel Instance of the model model used. Affine2D_F64 or Homography2D_F64
 * @param <I> Image input type.
 * @param <IT> Model model
 * @return  ImageMotion2D
 */
public static <I extends ImageBase<I>, IT extends InvertibleTransform> ImageMotion2D<I, IT> createMotion2D(int ransacIterations, double inlierThreshold, int outlierPrune, int absoluteMinimumTracks, double respawnTrackFraction, double respawnCoverageFraction, boolean refineEstimate, PointTracker<I> tracker, IT motionModel) {
    ModelManager<IT> manager;
    ModelGenerator<IT, AssociatedPair> fitter;
    DistanceFromModel<IT, AssociatedPair> distance;
    ModelFitter<IT, AssociatedPair> modelRefiner = null;
    if (motionModel instanceof Homography2D_F64) {
        GenerateHomographyLinear mf = new GenerateHomographyLinear(true);
        manager = (ModelManager) new ModelManagerHomography2D_F64();
        fitter = (ModelGenerator) mf;
        if (refineEstimate)
            modelRefiner = (ModelFitter) mf;
        distance = (DistanceFromModel) new DistanceHomographySq();
    } else if (motionModel instanceof Affine2D_F64) {
        manager = (ModelManager) new ModelManagerAffine2D_F64();
        GenerateAffine2D mf = new GenerateAffine2D();
        fitter = (ModelGenerator) mf;
        if (refineEstimate)
            modelRefiner = (ModelFitter) mf;
        distance = (DistanceFromModel) new DistanceAffine2DSq();
    } else if (motionModel instanceof Se2_F64) {
        manager = (ModelManager) new ModelManagerSe2_F64();
        MotionTransformPoint<Se2_F64, Point2D_F64> alg = new MotionSe2PointSVD_F64();
        GenerateSe2_AssociatedPair mf = new GenerateSe2_AssociatedPair(alg);
        fitter = (ModelGenerator) mf;
        distance = (DistanceFromModel) new DistanceSe2Sq();
    // no refine, already optimal
    } else {
        throw new RuntimeException("Unknown model type: " + motionModel.getClass().getSimpleName());
    }
    ModelMatcher<IT, AssociatedPair> modelMatcher = new Ransac(123123, manager, fitter, distance, ransacIterations, inlierThreshold);
    ImageMotionPointTrackerKey<I, IT> lowlevel = new ImageMotionPointTrackerKey<>(tracker, modelMatcher, modelRefiner, motionModel, outlierPrune);
    ImageMotionPtkSmartRespawn<I, IT> smartRespawn = new ImageMotionPtkSmartRespawn<>(lowlevel, absoluteMinimumTracks, respawnTrackFraction, respawnCoverageFraction);
    return new WrapImageMotionPtkSmartRespawn<>(smartRespawn);
}

Example 2 with ModelManagerHomography2D_F64

use of georegression.fitting.homography.ModelManagerHomography2D_F64 in project BoofCV by lessthanoptimal.

the class FactoryMultiViewRobust method homographyLMedS.

/**
 * Robust solution for estimating {@link Homography2D_F64} with {@link LeastMedianOfSquares LMedS}.  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 configLMedS Parameters for LMedS.  Can't be null.
 * @return Homography estimator
 */
public static LeastMedianOfSquares<Homography2D_F64, AssociatedPair> homographyLMedS(ConfigHomography homography, ConfigLMedS configLMedS) {
    if (homography == null)
        homography = new ConfigHomography();
    ModelManager<Homography2D_F64> manager = new ModelManagerHomography2D_F64();
    GenerateHomographyLinear modelFitter = new GenerateHomographyLinear(homography.normalize);
    DistanceHomographySq distance = new DistanceHomographySq();
    LeastMedianOfSquares<Homography2D_F64, AssociatedPair> lmeds = new LeastMedianOfSquares<>(configLMedS.randSeed, configLMedS.totalCycles, manager, modelFitter, distance);
    lmeds.setErrorFraction(configLMedS.errorFraction);
    return lmeds;
}

Example 3 with ModelManagerHomography2D_F64

use of georegression.fitting.homography.ModelManagerHomography2D_F64 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);
}