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BoofCV is an open source Java library for real-time computer vision and robotics applications.
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/*
* Copyright (c) 2021, 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.sfm;
import boofcv.abst.feature.detect.interest.PointDetectorTypes;
import boofcv.factory.feature.describe.ConfigDescribeRegion;
import boofcv.factory.feature.detect.interest.ConfigDetectInterestPoint;
import boofcv.factory.tracker.ConfigPointTracker;
import boofcv.struct.Configuration;
import boofcv.struct.pyramid.ConfigDiscreteLevels;
/**
* Configuration for {@link boofcv.alg.sfm.d3.VisOdomDualTrackPnP}
*
* @author Peter Abeles
*/
public class ConfigStereoDualTrackPnP implements Configuration {
/** Configuration for building and optimizing a local scene */
public ConfigVisOdomTrackPnP scene = new ConfigVisOdomTrackPnP();
/** Used to track features in each camera independently */
public ConfigPointTracker tracker = new ConfigPointTracker();
/** Feature descriptor for stereo association */
public ConfigDescribeRegion stereoDescribe = new ConfigDescribeRegion();
// TODO add in fancier sanity checks for stereo association
/** Radius used when computing feature descriptors for stereo matching */
public double stereoRadius = 11.0;
/** Tolerance for matching stereo features along epipolar line in Pixels */
public double epipolarTol = 1.5;
{
tracker.typeTracker = ConfigPointTracker.TrackerType.KLT;
tracker.klt.pyramidLevels = ConfigDiscreteLevels.minSize(40);
tracker.klt.pruneClose = true;
tracker.klt.toleranceFB = 3.0;
tracker.klt.templateRadius = 4;
tracker.detDesc.typeDetector = ConfigDetectInterestPoint.Type.POINT;
tracker.detDesc.detectPoint.type = PointDetectorTypes.SHI_TOMASI;
tracker.detDesc.detectPoint.shiTomasi.radius = 4;
tracker.detDesc.detectPoint.general.radius = 5;
stereoDescribe.type = ConfigDescribeRegion.Type.BRIEF;
stereoDescribe.brief.fixed = true;
}
@Override
public void checkValidity() {
scene.checkValidity();
if (scene.maxKeyFrames < 4)
throw new IllegalArgumentException("There must be at least 4 key frames");
tracker.checkValidity();
stereoDescribe.checkValidity();
}
public ConfigStereoDualTrackPnP setTo( ConfigStereoDualTrackPnP src ) {
this.scene.setTo(src.scene);
this.tracker.setTo(src.tracker);
this.stereoDescribe.setTo(src.stereoDescribe);
this.stereoRadius = src.stereoRadius;
this.epipolarTol = src.epipolarTol;
return this;
}
}
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