boofcv.factory.feature.tracker.FactoryPointTracker Maven / Gradle / Ivy
Go to download
Show more of this group Show more artifacts with this name
Show all versions of geo Show documentation
Show all versions of geo Show documentation
BoofCV is an open source Java library for real-time computer vision and robotics applications.
/*
* Copyright (c) 2011-2014, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package boofcv.factory.feature.tracker;
import boofcv.abst.feature.associate.*;
import boofcv.abst.feature.describe.ConfigSurfDescribe;
import boofcv.abst.feature.describe.DescribeRegionPoint;
import boofcv.abst.feature.describe.WrapDescribeBrief;
import boofcv.abst.feature.describe.WrapDescribePixelRegionNCC;
import boofcv.abst.feature.detdesc.DetectDescribeFusion;
import boofcv.abst.feature.detdesc.DetectDescribePoint;
import boofcv.abst.feature.detect.interest.ConfigFast;
import boofcv.abst.feature.detect.interest.ConfigFastHessian;
import boofcv.abst.feature.detect.interest.ConfigGeneralDetector;
import boofcv.abst.feature.detect.interest.InterestPointDetector;
import boofcv.abst.feature.orientation.ConfigAverageIntegral;
import boofcv.abst.feature.orientation.ConfigSlidingIntegral;
import boofcv.abst.feature.orientation.OrientationImage;
import boofcv.abst.feature.orientation.OrientationIntegral;
import boofcv.abst.feature.tracker.*;
import boofcv.abst.filter.derivative.ImageGradient;
import boofcv.alg.feature.associate.AssociateSurfBasic;
import boofcv.alg.feature.describe.DescribePointBrief;
import boofcv.alg.feature.describe.DescribePointPixelRegionNCC;
import boofcv.alg.feature.describe.DescribePointSurf;
import boofcv.alg.feature.describe.brief.FactoryBriefDefinition;
import boofcv.alg.feature.detect.intensity.GradientCornerIntensity;
import boofcv.alg.feature.detect.interest.EasyGeneralFeatureDetector;
import boofcv.alg.feature.detect.interest.GeneralFeatureDetector;
import boofcv.alg.filter.derivative.GImageDerivativeOps;
import boofcv.alg.interpolate.InterpolateRectangle;
import boofcv.alg.tracker.combined.CombinedTrackerScalePoint;
import boofcv.alg.tracker.klt.PkltConfig;
import boofcv.alg.transform.ii.GIntegralImageOps;
import boofcv.factory.feature.associate.FactoryAssociation;
import boofcv.factory.feature.describe.FactoryDescribePointAlgs;
import boofcv.factory.feature.describe.FactoryDescribeRegionPoint;
import boofcv.factory.feature.detdesc.FactoryDetectDescribe;
import boofcv.factory.feature.detect.intensity.FactoryIntensityPointAlg;
import boofcv.factory.feature.detect.interest.FactoryDetectPoint;
import boofcv.factory.feature.detect.interest.FactoryInterestPoint;
import boofcv.factory.feature.orientation.FactoryOrientation;
import boofcv.factory.feature.orientation.FactoryOrientationAlgs;
import boofcv.factory.filter.blur.FactoryBlurFilter;
import boofcv.factory.filter.derivative.FactoryDerivative;
import boofcv.factory.interpolate.FactoryInterpolation;
import boofcv.factory.tracker.FactoryTrackerAlg;
import boofcv.factory.transform.pyramid.FactoryPyramid;
import boofcv.struct.feature.*;
import boofcv.struct.image.ImageSingleBand;
import boofcv.struct.pyramid.PyramidDiscrete;
import java.util.Random;
/**
* Factory for creating trackers which implement {@link boofcv.abst.feature.tracker.PointTracker}. These trackers
* are intended for use in SFM applications. Some features which individual trackers can provide are lost when
* using the high level interface {@link PointTracker}. To create low level tracking algorithms see
* {@link FactoryTrackerAlg}
*
* @see FactoryTrackerAlg
*
* @author Peter Abeles
*/
public class FactoryPointTracker {
/**
* Pyramid KLT feature tracker.
*
* @see boofcv.alg.tracker.klt.PyramidKltTracker
*
* @param scaling Scales in the image pyramid. Recommend [1,2,4] or [2,4]
* @param configExtract Configuration for extracting features
* @param featureRadius Size of the tracked feature. Try 3 or 5
* @param imageType Input image type.
* @param derivType Image derivative type.
* @return KLT based tracker.
*/
public static
PointTracker klt(int scaling[], ConfigGeneralDetector configExtract, int featureRadius,
Class imageType, Class derivType) {
PkltConfig config = new PkltConfig();
config.pyramidScaling = scaling;
config.templateRadius = featureRadius;
return klt(config, configExtract, imageType, derivType );
}
/**
* Pyramid KLT feature tracker.
*
* @see boofcv.alg.tracker.klt.PyramidKltTracker
*
* @param config Config for the tracker. Try PkltConfig.createDefault().
* @param configExtract Configuration for extracting features
* @return KLT based tracker.
*/
public static
PointTracker klt(PkltConfig config, ConfigGeneralDetector configExtract,
Class imageType, Class derivType ) {
if( derivType == null )
derivType = GImageDerivativeOps.getDerivativeType(imageType);
if( config == null ) {
config = new PkltConfig();
}
if( configExtract == null ) {
configExtract = new ConfigGeneralDetector();
}
GeneralFeatureDetector detector = createShiTomasi(configExtract, derivType);
InterpolateRectangle interpInput = FactoryInterpolation.bilinearRectangle(imageType);
InterpolateRectangle interpDeriv = FactoryInterpolation.bilinearRectangle(derivType);
ImageGradient gradient = FactoryDerivative.sobel(imageType, derivType);
PyramidDiscrete pyramid = FactoryPyramid.discreteGaussian(config.pyramidScaling,-1,2,true,imageType);
return new PointTrackerKltPyramid(config.config,config.templateRadius,pyramid,detector,
gradient,interpInput,interpDeriv,derivType);
}
/**
* Creates a tracker which detects Fast-Hessian features and describes them with SURF using the faster variant
* of SURF.
*
* @see DescribePointSurf
* @see boofcv.abst.feature.tracker.DdaManagerDetectDescribePoint
*
* @param configDetector Configuration for SURF detector
* @param configDescribe Configuration for SURF descriptor
* @param configOrientation Configuration for orientation
* @param imageType Type of image the input is.
* @return SURF based tracker.
*/
// TODO remove maxTracks? Use number of detected instead
public static
PointTracker dda_FH_SURF_Fast(
ConfigFastHessian configDetector ,
ConfigSurfDescribe.Speed configDescribe ,
ConfigAverageIntegral configOrientation ,
Class imageType)
{
ScoreAssociation score = FactoryAssociation.scoreEuclidean(TupleDesc_F64.class, true);
AssociateSurfBasic assoc = new AssociateSurfBasic(FactoryAssociation.greedy(score, 5, true));
AssociateDescription2D generalAssoc =
new AssociateDescTo2D(new WrapAssociateSurfBasic(assoc));
DetectDescribePoint fused =
FactoryDetectDescribe.surfFast(configDetector, configDescribe, configOrientation,imageType);
DdaManagerDetectDescribePoint manager = new DdaManagerDetectDescribePoint(fused);
return new DetectDescribeAssociate(manager, generalAssoc,false);
}
/**
* Creates a tracker which detects Fast-Hessian features and describes them with SURF using the faster variant
* of SURF.
*
* @see DescribePointSurf
* @see boofcv.abst.feature.tracker.DdaManagerDetectDescribePoint
*
* @param configDetector Configuration for SURF detector
* @param configDescribe Configuration for SURF descriptor
* @param configOrientation Configuration for orientation
* @param imageType Type of image the input is.
* @return SURF based tracker.
*/
// TODO remove maxTracks? Use number of detected instead
public static
PointTracker dda_FH_SURF_Stable(
ConfigFastHessian configDetector ,
ConfigSurfDescribe.Stability configDescribe ,
ConfigSlidingIntegral configOrientation ,
Class imageType)
{
ScoreAssociation score = FactoryAssociation.scoreEuclidean(TupleDesc_F64.class, true);
AssociateSurfBasic assoc = new AssociateSurfBasic(FactoryAssociation.greedy(score, 5, true));
AssociateDescription2D generalAssoc =
new AssociateDescTo2D(new WrapAssociateSurfBasic(assoc));
DetectDescribePoint fused =
FactoryDetectDescribe.surfStable(configDetector,configDescribe,configOrientation,imageType);
DdaManagerDetectDescribePoint manager = new DdaManagerDetectDescribePoint(fused);
return new DetectDescribeAssociate(manager, generalAssoc,false);
}
/**
* Creates a tracker which detects Shi-Tomasi corner features and describes them with BRIEF.
*
* @see boofcv.alg.feature.detect.intensity.ShiTomasiCornerIntensity
* @see DescribePointBrief
* @see boofcv.abst.feature.tracker.DdaManagerDetectDescribePoint
*
* @param maxAssociationError Maximum allowed association error. Try 200.
* @param configExtract Configuration for extracting features
* @param imageType Type of image being processed.
* @param derivType Type of image used to store the image derivative. null == use default
*/
public static
PointTracker dda_ST_BRIEF(int maxAssociationError,
ConfigGeneralDetector configExtract,
Class imageType, Class derivType)
{
if( derivType == null )
derivType = GImageDerivativeOps.getDerivativeType(imageType);
DescribePointBrief brief = FactoryDescribePointAlgs.brief(FactoryBriefDefinition.gaussian2(new Random(123), 16, 512),
FactoryBlurFilter.gaussian(imageType, 0, 4));
GeneralFeatureDetector detectPoint = createShiTomasi(configExtract, derivType);
EasyGeneralFeatureDetector easy = new EasyGeneralFeatureDetector(detectPoint,imageType,derivType);
ScoreAssociateHamming_B score = new ScoreAssociateHamming_B();
AssociateDescription2D association =
new AssociateDescTo2D(FactoryAssociation.greedy(score, maxAssociationError, true));
DdaManagerGeneralPoint manager =
new DdaManagerGeneralPoint(easy,new WrapDescribeBrief(brief,imageType),1.0);
return new DetectDescribeAssociate(manager, association,false);
}
/**
* Creates a tracker which detects FAST corner features and describes them with BRIEF.
*
* @see boofcv.alg.feature.detect.intensity.FastCornerIntensity
* @see DescribePointBrief
* @see boofcv.abst.feature.tracker.DdaManagerDetectDescribePoint
*
* @param configFast Configuration for FAST detector
* @param configExtract Configuration for extracting features
* @param maxAssociationError Maximum allowed association error. Try 200.
* @param imageType Type of image being processed.
*/
public static
PointTracker dda_FAST_BRIEF(ConfigFast configFast,
ConfigGeneralDetector configExtract,
int maxAssociationError,
Class imageType )
{
DescribePointBrief brief = FactoryDescribePointAlgs.brief(FactoryBriefDefinition.gaussian2(new Random(123), 16, 512),
FactoryBlurFilter.gaussian(imageType, 0, 4));
GeneralFeatureDetector corner = FactoryDetectPoint.createFast(configFast, configExtract, imageType);
EasyGeneralFeatureDetector easy = new EasyGeneralFeatureDetector(corner,imageType,null);
ScoreAssociateHamming_B score = new ScoreAssociateHamming_B();
AssociateDescription2D association =
new AssociateDescTo2D(
FactoryAssociation.greedy(score, maxAssociationError, true));
DdaManagerGeneralPoint manager =
new DdaManagerGeneralPoint(easy,new WrapDescribeBrief(brief,imageType),1.0);
return new DetectDescribeAssociate(manager, association,false);
}
/**
* Creates a tracker which detects Shi-Tomasi corner features and describes them with NCC.
*
* @see boofcv.alg.feature.detect.intensity.ShiTomasiCornerIntensity
* @see DescribePointPixelRegionNCC
* @see boofcv.abst.feature.tracker.DdaManagerDetectDescribePoint
*
* @param configExtract Configuration for extracting features
* @param describeRadius Radius of the region being described. Try 2.
* @param imageType Type of image being processed.
* @param derivType Type of image used to store the image derivative. null == use default */
public static
PointTracker dda_ST_NCC(ConfigGeneralDetector configExtract, int describeRadius,
Class imageType, Class derivType) {
if( derivType == null )
derivType = GImageDerivativeOps.getDerivativeType(imageType);
int w = 2*describeRadius+1;
DescribePointPixelRegionNCC alg = FactoryDescribePointAlgs.pixelRegionNCC(w, w, imageType);
GeneralFeatureDetector corner = createShiTomasi(configExtract, derivType);
EasyGeneralFeatureDetector easy = new EasyGeneralFeatureDetector(corner,imageType,derivType);
ScoreAssociateNccFeature score = new ScoreAssociateNccFeature();
AssociateDescription2D association =
new AssociateDescTo2D(
FactoryAssociation.greedy(score, Double.MAX_VALUE, true));
DdaManagerGeneralPoint manager =
new DdaManagerGeneralPoint(easy,new WrapDescribePixelRegionNCC(alg,imageType),1.0);
return new DetectDescribeAssociate(manager, association,false);
}
/**
* Creates a tracker which uses the detect, describe, associate architecture.
*
* @param detector Interest point detector.
* @param orientation Optional orientation estimation algorithm. Can be null.
* @param describe Region description.
* @param associate Description association.
* @param updateDescription After a track has been associated should the description be changed? Try false.
* @param Type of input image.
* @param Type of region description
* @return tracker
*/
public static
DetectDescribeAssociate dda(InterestPointDetector detector,
OrientationImage orientation ,
DescribeRegionPoint describe,
AssociateDescription2D associate ,
boolean updateDescription ) {
DetectDescribeFusion fused =
new DetectDescribeFusion(detector,orientation,describe);
DdaManagerDetectDescribePoint manager =
new DdaManagerDetectDescribePoint(fused);
DetectDescribeAssociate dat =
new DetectDescribeAssociate(manager, associate,updateDescription);
return dat;
}
public static
DetectDescribeAssociate dda( DetectDescribePoint detDesc,
AssociateDescription2D associate ,
boolean updateDescription ) {
DdaManagerDetectDescribePoint manager =
new DdaManagerDetectDescribePoint(detDesc);
DetectDescribeAssociate dat =
new DetectDescribeAssociate(manager, associate,updateDescription);
return dat;
}
/**
* Creates a tracker which detects Fast-Hessian features, describes them with SURF, nominally tracks them using KLT.
*
* @see DescribePointSurf
* @see boofcv.abst.feature.tracker.DdaManagerDetectDescribePoint
*
* @param kltConfig Configuration for KLT tracker
* @param reactivateThreshold Tracks are reactivated after this many have been dropped. Try 10% of maxMatches
* @param configDetector Configuration for SURF detector
* @param configDescribe Configuration for SURF descriptor
* @param configOrientation Configuration for region orientation
* @param imageType Type of image the input is.
* @param Input image type.
* @return SURF based tracker.
*/
public static
PointTracker combined_FH_SURF_KLT( PkltConfig kltConfig ,
int reactivateThreshold ,
ConfigFastHessian configDetector ,
ConfigSurfDescribe.Stability configDescribe ,
ConfigSlidingIntegral configOrientation ,
Class imageType) {
ScoreAssociation score = FactoryAssociation.defaultScore(TupleDesc_F64.class);
AssociateSurfBasic assoc = new AssociateSurfBasic(FactoryAssociation.greedy(score, 100000, true));
AssociateDescription generalAssoc = new WrapAssociateSurfBasic(assoc);
DetectDescribePoint fused =
FactoryDetectDescribe.surfStable(configDetector, configDescribe, configOrientation,imageType);
return combined(fused,generalAssoc, kltConfig,reactivateThreshold, imageType);
}
/**
* Creates a tracker which detects Shi-Tomasi corner features, describes them with SURF, and
* nominally tracks them using KLT.
*
* @see boofcv.alg.feature.detect.intensity.ShiTomasiCornerIntensity
* @see DescribePointSurf
* @see boofcv.abst.feature.tracker.DdaManagerDetectDescribePoint
*
* @param configExtract Configuration for extracting features
* @param kltConfig Configuration for KLT
* @param reactivateThreshold Tracks are reactivated after this many have been dropped. Try 10% of maxMatches
* @param configDescribe Configuration for SURF descriptor
* @param configOrientation Configuration for region orientation. If null then orientation isn't estimated
* @param imageType Type of image the input is.
* @param derivType Image derivative type. @return SURF based tracker.
*/
public static
PointTracker combined_ST_SURF_KLT(ConfigGeneralDetector configExtract,
PkltConfig kltConfig,
int reactivateThreshold,
ConfigSurfDescribe.Stability configDescribe,
ConfigSlidingIntegral configOrientation,
Class imageType,
Class derivType) {
if( derivType == null )
derivType = GImageDerivativeOps.getDerivativeType(imageType);
GeneralFeatureDetector corner = createShiTomasi(configExtract, derivType);
InterestPointDetector detector = FactoryInterestPoint.wrapPoint(corner, 1, imageType, derivType);
DescribeRegionPoint regionDesc
= FactoryDescribeRegionPoint.surfStable(configDescribe, imageType);
ScoreAssociation score = FactoryAssociation.scoreEuclidean(TupleDesc_F64.class, true);
AssociateSurfBasic assoc = new AssociateSurfBasic(FactoryAssociation.greedy(score, 100000, true));
AssociateDescription generalAssoc = new WrapAssociateSurfBasic(assoc);
OrientationImage orientation = null;
if( configOrientation != null ) {
Class integralType = GIntegralImageOps.getIntegralType(imageType);
OrientationIntegral orientationII = FactoryOrientationAlgs.sliding_ii(configOrientation, integralType);
orientation = FactoryOrientation.convertImage(orientationII,imageType);
}
return combined(detector,orientation,regionDesc,generalAssoc, kltConfig,reactivateThreshold,
imageType);
}
/**
* Creates a tracker that is a hybrid between KLT and Detect-Describe-Associate (DDA) trackers.
*
* @see CombinedTrackerScalePoint
*
* @param detector Feature detector.
* @param orientation Optional feature orientation. Can be null.
* @param describe Feature description
* @param associate Association algorithm.
* @param kltConfig Configuration for KLT tracker
* @param reactivateThreshold Tracks are reactivated after this many have been dropped. Try 10% of maxMatches
* @param imageType Input image type. @return Feature tracker
*/
public static
PointTracker combined(InterestPointDetector detector,
OrientationImage orientation,
DescribeRegionPoint describe,
AssociateDescription associate,
PkltConfig kltConfig ,
int reactivateThreshold,
Class imageType)
{
DetectDescribeFusion fused = new DetectDescribeFusion(detector,orientation,describe);
return combined(fused,associate, kltConfig, reactivateThreshold,imageType);
}
/**
* Creates a tracker that is a hybrid between KLT and Detect-Describe-Associate (DDA) trackers.
*
* @see CombinedTrackerScalePoint
*
* @param detector Feature detector and describer.
* @param associate Association algorithm.
* @param kltConfig Configuration for KLT tracker
* @param reactivateThreshold Tracks are reactivated after this many have been dropped. Try 10% of maxMatches
* @param imageType Input image type. @return Feature tracker
*/
public static
PointTracker combined(DetectDescribePoint detector,
AssociateDescription associate,
PkltConfig kltConfig ,
int reactivateThreshold, Class imageType )
{
Class derivType = GImageDerivativeOps.getDerivativeType(imageType);
if( kltConfig == null ) {
kltConfig = new PkltConfig();
}
CombinedTrackerScalePoint tracker =
FactoryTrackerAlg.combined(detector,associate, kltConfig,imageType,derivType);
return new PointTrackerCombined(tracker,reactivateThreshold,imageType,derivType);
}
public static
PointTracker dda(GeneralFeatureDetector detector,
DescribeRegionPoint describe,
AssociateDescription2D associate,
double scale,
Class imageType) {
EasyGeneralFeatureDetector easy = new EasyGeneralFeatureDetector(detector,imageType,null);
DdaManagerGeneralPoint manager =
new DdaManagerGeneralPoint(easy,describe,scale);
return new DetectDescribeAssociate(manager,associate,false);
}
/**
* Creates a Shi-Tomasi corner detector specifically designed for SFM. Smaller feature radius work better.
* Variable detectRadius to control the number of features. When larger features are used weighting should
* be set to true, but because this is so small, it is set to false
*/
public static
GeneralFeatureDetector createShiTomasi(ConfigGeneralDetector config ,
Class derivType)
{
GradientCornerIntensity cornerIntensity = FactoryIntensityPointAlg.shiTomasi(1, false, derivType);
return FactoryDetectPoint.createGeneral(cornerIntensity, config );
}
}