View source for Example Visual Odometry Depth


This example demonstrates how to estimate the camera's ego motion using an RGB-D sensor, such as the Kinect, which contains visual and depth information.

Example Code:
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.39/examples/src/main/java/boofcv/examples/sfm/ExampleVisualOdometryDepth.java ExampleVisualOdometryDepth.java]

Concepts:
* RGB-D

Relevant Videos:
* [http://www.youtube.com/watch?v=kOGXsf1tP3A| YouTube]

Related Examples:
* [[Example Visual Odometry Monocular Plane| Visual Odometry Monocular Plane]]
* [[Example_Stereo_Visual_Odometry| Visual Odometry Stereo]]

= Example Code =

<syntaxhighlight lang="java">
/**
 * Bare bones example showing how to estimate the camera's ego-motion using a depth camera system, e.g. Kinect.
 * Additional information on the scene can be optionally extracted from the algorithm if it implements AccessPointTracks3D.
 *
 * @author Peter Abeles
 */
public class ExampleVisualOdometryDepth {
	public static void main( String[] args ) {
		MediaManager media = DefaultMediaManager.INSTANCE;

		String directory = UtilIO.pathExample("kinect/straight");

		// load camera description and the video sequence
		VisualDepthParameters param = CalibrationIO.load(
				media.openFile(new File(directory, "visualdepth.yaml").getPath()));

		// specify how the image features are going to be tracked
		ConfigRgbDepthTrackPnP config = new ConfigRgbDepthTrackPnP();
		config.depthScale = 1e-3; // convert depth image distance units to meters

		config.tracker.typeTracker = ConfigPointTracker.TrackerType.KLT;
		config.tracker.detDesc.detectPoint.type = PointDetectorTypes.SHI_TOMASI;
		config.tracker.detDesc.detectPoint.shiTomasi.radius = 3;
		config.tracker.detDesc.detectPoint.general.maxFeatures = 600;
		config.tracker.detDesc.detectPoint.general.radius = 3;
		config.tracker.detDesc.detectPoint.general.threshold = 1;

		// declares the algorithm
		DepthVisualOdometry<GrayU8, GrayU16> visualOdometry =
				FactoryVisualOdometry.rgbDepthPnP(config, GrayU8.class, GrayU16.class);

		// Pass in intrinsic/extrinsic calibration. This can be changed in the future.
		visualOdometry.setCalibration(param.visualParam, new DoNothing2Transform2_F32());

		// Process the video sequence and output the location plus number of inliers
		SimpleImageSequence<GrayU8> videoVisual = media.openVideo(
				new File(directory, "rgb.mjpeg").getPath(), ImageType.single(GrayU8.class));
		SimpleImageSequence<GrayU16> videoDepth = media.openVideo(
				new File(directory, "depth.mpng").getPath(), ImageType.single(GrayU16.class));

		long startTime = System.nanoTime();
		while (videoVisual.hasNext()) {
			GrayU8 visual = videoVisual.next();
			GrayU16 depth = videoDepth.next();

			if (!visualOdometry.process(visual, depth)) {
				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, %s\n", T.x, T.y, T.z, trackStats(visualOdometry));
		}
		System.out.printf("FPS %4.2f\n", videoVisual.getFrameNumber()/((System.nanoTime() - startTime)*1e-9));
	}
}
</syntaxhighlight>