Difference between revisions of "Example Point Cloud Depth Image"

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Example Code:
Example Code:
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/geometry/ExampleDepthPointCloud.java ExampleDepthPointCloud.java]
* [https://github.com/lessthanoptimal/BoofCV/blob/v0.40/examples/src/main/java/boofcv/examples/geometry/ExampleDepthPointCloud.java ExampleDepthPointCloud.java]


Concepts:
Concepts:
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VisualDepthParameters param = CalibrationIO.load(nameCalib);
VisualDepthParameters param = CalibrationIO.load(nameCalib);


BufferedImage buffered = UtilImageIO.loadImage(nameRgb);
BufferedImage buffered = UtilImageIO.loadImageNotNull(nameRgb);
Planar<GrayU8> rgb = ConvertBufferedImage.convertFromPlanar(buffered, null, true, GrayU8.class);
Planar<GrayU8> rgb = ConvertBufferedImage.convertFromPlanar(buffered, null, true, GrayU8.class);
GrayU16 depth = ConvertBufferedImage.convertFrom(UtilImageIO.loadImage(nameDepth), null, GrayU16.class);
GrayU16 depth = ConvertBufferedImage.convertFrom(UtilImageIO.loadImageNotNull(nameDepth), null, GrayU16.class);


var cloud = new DogArray<>(Point3D_F64::new);
var cloud = new DogArray<>(Point3D_F64::new);

Latest revision as of 15:54, 17 January 2022

This example demonstrates how to create a 3D point cloud from a RGB-D sensor, such as the Kinect, and visualize it. RGB-D sensors have both visual and depth information. In this example the depth information is stored in a 16-bit image and the visual image in a standard color image. Calibration matching RGB an depth pixels to each other has already been done by the sensor.

Example Code:

Concepts:

  • RGB-D
  • Point clouds

Related Examples:

Example Code

/**
 * Example of how to create a point cloud from a RGB-D (Kinect) sensor. Data is loaded from two files, one for the
 * visual image and one for the depth image.
 *
 * @author Peter Abeles
 */
public class ExampleDepthPointCloud {
	public static void main( String[] args ) {
		String nameRgb = UtilIO.pathExample("kinect/basket/basket_rgb.png");
		String nameDepth = UtilIO.pathExample("kinect/basket/basket_depth.png");
		String nameCalib = UtilIO.pathExample("kinect/basket/visualdepth.yaml");

		VisualDepthParameters param = CalibrationIO.load(nameCalib);

		BufferedImage buffered = UtilImageIO.loadImageNotNull(nameRgb);
		Planar<GrayU8> rgb = ConvertBufferedImage.convertFromPlanar(buffered, null, true, GrayU8.class);
		GrayU16 depth = ConvertBufferedImage.convertFrom(UtilImageIO.loadImageNotNull(nameDepth), null, GrayU16.class);

		var cloud = new DogArray<>(Point3D_F64::new);
		var cloudColor = new DogArray<>(() -> new int[3]);

		VisualDepthOps.depthTo3D(param.visualParam, rgb, depth, cloud, cloudColor);

		PointCloudViewer viewer = VisualizeData.createPointCloudViewer();
		viewer.setCameraHFov(PerspectiveOps.computeHFov(param.visualParam));
		viewer.setTranslationStep(15);

		for (int i = 0; i < cloud.size; i++) {
			Point3D_F64 p = cloud.get(i);
			int[] color = cloudColor.get(i);
			int c = (color[0] << 16) | (color[1] << 8) | color[2];
			viewer.addPoint(p.x, p.y, p.z, c);
		}
		viewer.getComponent().setPreferredSize(new Dimension(rgb.width, rgb.height));

		// ---------- Display depth image
		// use the actual max value in the image to maximize its appearance
		int maxValue = ImageStatistics.max(depth);
		BufferedImage depthOut = VisualizeImageData.disparity(depth, null, maxValue, 0);
		ShowImages.showWindow(depthOut, "Depth Image", true);

		// ---------- Display colorized point cloud
		ShowImages.showWindow(viewer.getComponent(), "Point Cloud", true);
		System.out.println("Total points = " + cloud.size);
	}
}