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/*
* Copyright (c) 2011-2018, 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.examples.sfm;
import boofcv.abst.feature.detect.interest.ConfigGeneralDetector;
import boofcv.abst.feature.disparity.StereoDisparitySparse;
import boofcv.abst.feature.tracker.PointTrackerTwoPass;
import boofcv.abst.sfm.AccessPointTracks3D;
import boofcv.abst.sfm.d3.StereoVisualOdometry;
import boofcv.alg.tracker.klt.PkltConfig;
import boofcv.factory.feature.disparity.FactoryStereoDisparity;
import boofcv.factory.feature.tracker.FactoryPointTrackerTwoPass;
import boofcv.factory.sfm.FactoryVisualOdometry;
import boofcv.io.MediaManager;
import boofcv.io.UtilIO;
import boofcv.io.calibration.CalibrationIO;
import boofcv.io.image.SimpleImageSequence;
import boofcv.io.wrapper.DefaultMediaManager;
import boofcv.struct.calib.StereoParameters;
import boofcv.struct.image.GrayS16;
import boofcv.struct.image.GrayU8;
import boofcv.struct.image.ImageType;
import georegression.struct.point.Vector3D_F64;
import georegression.struct.se.Se3_F64;
import java.io.File;
/**
* Bare bones example showing how to estimate the camera's ego-motion using a stereo camera system. Additional
* information on the scene can be optionally extracted from the algorithm if it implements AccessPointTracks3D.
*
* @author Peter Abeles
*/
public class ExampleVisualOdometryStereo {
public static void main( String args[] ) {
MediaManager media = DefaultMediaManager.INSTANCE;
String directory = UtilIO.pathExample("vo/backyard/");
// load camera description and the video sequence
StereoParameters stereoParam = CalibrationIO.load(media.openFile(new File(directory , "stereo.yaml").getPath()));
SimpleImageSequence video1 = media.openVideo(
new File(directory , "left.mjpeg").getPath(), ImageType.single(GrayU8.class));
SimpleImageSequence video2 = media.openVideo(
new File(directory,"right.mjpeg").getPath(), ImageType.single(GrayU8.class));
// specify how the image features are going to be tracked
PkltConfig configKlt = new PkltConfig();
configKlt.pyramidScaling = new int[]{1, 2, 4, 8};
configKlt.templateRadius = 3;
PointTrackerTwoPass tracker =
FactoryPointTrackerTwoPass.klt(configKlt, new ConfigGeneralDetector(600, 3, 1),
GrayU8.class, GrayS16.class);
// computes the depth of each point
StereoDisparitySparse disparity =
FactoryStereoDisparity.regionSparseWta(0, 150, 3, 3, 30, -1, true, GrayU8.class);
// declares the algorithm
StereoVisualOdometry visualOdometry = FactoryVisualOdometry.stereoDepth(1.5,120, 2,200,50,true,
disparity, tracker, GrayU8.class);
// Pass in intrinsic/extrinsic calibration. This can be changed in the future.
visualOdometry.setCalibration(stereoParam);
// Process the video sequence and output the location plus number of inliers
while( video1.hasNext() ) {
GrayU8 left = video1.next();
GrayU8 right = video2.next();
if( !visualOdometry.process(left,right) ) {
throw new RuntimeException("VO Failed!");
}
Se3_F64 leftToWorld = visualOdometry.getCameraToWorld();
Vector3D_F64 T = leftToWorld.getT();
System.out.printf("Location %8.2f %8.2f %8.2f inliers %s\n", T.x, T.y, T.z, inlierPercent(visualOdometry));
}
}
/**
* If the algorithm implements AccessPointTracks3D, then count the number of inlier features
* and return a string.
*/
public static String inlierPercent(StereoVisualOdometry alg) {
if( !(alg instanceof AccessPointTracks3D))
return "";
AccessPointTracks3D access = (AccessPointTracks3D)alg;
int count = 0;
int N = access.getAllTracks().size();
for( int i = 0; i < N; i++ ) {
if( access.isInlier(i) )
count++;
}
return String.format("%%%5.3f", 100.0 * count / N);
}
}