Example Visual Odometry Monocular Plane

This example demonstrates how to estimate the camera's ego motion using a single camera and known plane. Since the plane's relative location to the camera is known there is no scale ambiguity, like there is with a more general single camera solution.

Example Code:

• ExampleVisualOdometryMonocularPlane.java

Concepts:

• Plane/Homography

Related Examples:

• Visual Odometry Depth
• Visual Odometry Stereo

Example Code

/**
 * Bare bones example showing how to estimate the camera's ego-motion using a single camera and a known
 * plane. Additional information on the scene can be optionally extracted from the algorithm,
 * if it implements AccessPointTracks3D.
 *
 * @author Peter Abeles
 */
public class ExampleVisualOdometryMonocularPlane {
	public static void main( String[] args ) {
		MediaManager media = DefaultMediaManager.INSTANCE;

		String directory = UtilIO.pathExample("vo/drc/");

		// load camera description and the video sequence
		MonoPlaneParameters calibration = CalibrationIO.load(
				media.openFile(new File(directory, "mono_plane.yaml").getPath()));
		SimpleImageSequence<GrayU8> video = media.openVideo(
				new File(directory, "left.mjpeg").getPath(), ImageType.single(GrayU8.class));

		// specify how the image features are going to be tracked
		ConfigPKlt configKlt = new ConfigPKlt();
		configKlt.pyramidLevels = ConfigDiscreteLevels.levels(4);
		configKlt.templateRadius = 3;
		ConfigPointDetector configDetector = new ConfigPointDetector();
		configDetector.type = PointDetectorTypes.SHI_TOMASI;
		configDetector.general.maxFeatures = 600;
		configDetector.general.radius = 3;
		configDetector.general.threshold = 1;

		PointTracker<GrayU8> tracker = FactoryPointTracker.klt(configKlt, configDetector, GrayU8.class, null);

		// declares the algorithm
		MonocularPlaneVisualOdometry<GrayU8> visualOdometry =
				FactoryVisualOdometry.monoPlaneInfinity(75, 2, 1.5, 200, tracker, ImageType.single(GrayU8.class));

		// Pass in intrinsic/extrinsic calibration.  This can be changed in the future.
		visualOdometry.setCalibration(calibration);

		// Process the video sequence and output the location plus number of inliers
		while (video.hasNext()) {
			GrayU8 image = video.next();

			if (!visualOdometry.process(image)) {
				System.out.println("Fault!");
				visualOdometry.reset();
			}

			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( VisualOdometry<?> alg ) {
		if (!(alg instanceof AccessPointTracks3D))
			return "";

		AccessPointTracks3D access = (AccessPointTracks3D)alg;

		int count = 0;
		int N = access.getTotalTracks();
		for (int i = 0; i < N; i++) {
			if (access.isTrackInlier(i))
				count++;
		}

		return String.format("%%%5.3f", 100.0*count/N);
	}
}