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BoofCV is an open source Java library for real-time computer vision and robotics applications.
/*
* Copyright (c) 2011-2017, 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.alg.feature.associate;
import boofcv.abst.feature.associate.AssociateDescription2D;
import boofcv.abst.feature.associate.ScoreAssociation;
import boofcv.struct.feature.AssociatedIndex;
import boofcv.struct.feature.MatchScoreType;
import boofcv.struct.feature.TupleDesc;
import georegression.struct.point.Point2D_F64;
import org.ddogleg.struct.FastQueue;
import org.ddogleg.struct.GrowQueue_I32;
/**
* Association for a stereo pair where the source is the left camera and the destination is the right camera. Pixel
* coordinates are rectified and associations are only considered if the two observations are within tolerance
* of each other along the y-axis and that the left observation's x-coordinate is greater than the right.
*
* @author Peter Abeles
*/
public class AssociateStereo2D
extends StereoConsistencyCheck
implements AssociateDescription2D
{
// computes match score between two descriptions
private ScoreAssociation scorer;
// storage for associated features
private FastQueue matches = new FastQueue<>(AssociatedIndex.class, true);
// stores indexes of unassociated source features
private GrowQueue_I32 unassociatedSrc = new GrowQueue_I32();
// creates a list of unassociated features from the list of matches
private FindUnassociated unassociated = new FindUnassociated();
// maximum allowed score when matching descriptors
private double scoreThreshold = Double.MAX_VALUE;
// stores rectified coordinates of observations in left and right images
private FastQueue locationLeft = new FastQueue<>(Point2D_F64.class, true);
private FastQueue locationRight = new FastQueue<>(Point2D_F64.class, true);
// stores reference to descriptions in left and right iamges
private FastQueue descriptionsLeft;
private FastQueue descriptionsRight;
public AssociateStereo2D( ScoreAssociation scorer , double locationTolerance , Class descType )
{
super(locationTolerance,locationTolerance);
this.scorer = scorer;
descriptionsLeft = new FastQueue<>(descType, false);
descriptionsRight = new FastQueue<>(descType, false);
}
/**
* Converts location into rectified coordinates and saved a reference to the description.
*/
@Override
public void setSource(FastQueue location, FastQueue descriptions) {
locationLeft.reset();
for( int i = 0; i < location.size; i++ ) {
Point2D_F64 orig = location.get(i);
Point2D_F64 rectified = locationLeft.grow();
leftImageToRect.compute(orig.x,orig.y,rectified);
}
this.descriptionsLeft = descriptions;
}
/**
* Converts location into rectified coordinates and saved a reference to the description.
*/
@Override
public void setDestination(FastQueue location, FastQueue descriptions) {
locationRight.reset();
for( int i = 0; i < location.size; i++ ) {
Point2D_F64 orig = location.get(i);
Point2D_F64 rectified = locationRight.grow();
rightImageToRect.compute(orig.x,orig.y,rectified);
}
this.descriptionsRight = descriptions;
}
@Override
public void associate() {
matches.reset();
unassociatedSrc.reset();
for( int i = 0; i < locationLeft.size; i++ ) {
Point2D_F64 left = locationLeft.get(i);
Desc descLeft = descriptionsLeft.get(i);
int bestIndex = -1;
double bestScore = scoreThreshold;
for( int j = 0; j < locationRight.size; j++ ) {
Point2D_F64 right = locationRight.get(j);
if( checkRectified(left,right) ) {
double dist = scorer.score(descLeft, descriptionsRight.get(j));
if( dist < bestScore ) {
bestScore = dist;
bestIndex = j;
}
}
}
if( bestIndex >= 0 ) {
matches.grow().setAssociation(i,bestIndex,bestScore);
} else {
unassociatedSrc.push(i);
}
}
}
@Override
public FastQueue getMatches() {
return matches;
}
@Override
public GrowQueue_I32 getUnassociatedSource() {
return unassociatedSrc;
}
@Override
public GrowQueue_I32 getUnassociatedDestination() {
return unassociated.checkDestination(matches,locationRight.size);
}
@Override
public void setThreshold(double score) {
this.scoreThreshold = score;
}
@Override
public MatchScoreType getScoreType() {
return scorer.getScoreType();
}
@Override
public boolean uniqueSource() {
return true;
}
@Override
public boolean uniqueDestination() {
return false;
}
}
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