Example Stereo Mesh

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Shows you how to convert a disparity image into a 3D mesh. Meshes are typically easier to view in 3rd party libraries.

Example Code:


  • Stereo Disparity
  • Filtering

Related Examples:

Example Code

 * Example showing how you can convert a disparity image into a 3D mesh.
 * @author Peter Abeles
public class ExampleStereoMesh {
	static int disparityMin = 5;
	static int disparityRange = 60;

	public static void main( String[] args ) {
		String calibDir = UtilIO.pathExample("calibration/stereo/Bumblebee2_Chess/");
		String imageDir = UtilIO.pathExample("stereo/");

		StereoParameters param = CalibrationIO.load(new File(calibDir, "stereo.yaml"));

		// load and convert images into a BoofCV format
		BufferedImage origLeft = UtilImageIO.loadImage(imageDir, "sundial01_left.jpg");
		BufferedImage origRight = UtilImageIO.loadImage(imageDir, "sundial01_right.jpg");

		GrayU8 distLeft = ConvertBufferedImage.convertFrom(origLeft, (GrayU8)null);
		GrayU8 distRight = ConvertBufferedImage.convertFrom(origRight, (GrayU8)null);

		// rectify images
		GrayU8 rectLeft = distLeft.createSameShape();
		GrayU8 rectRight = distRight.createSameShape();

		// Using a previous example, rectify then compute the disparity image
		RectifyCalibrated rectifier = ExampleStereoDisparity.rectify(distLeft, distRight, param, rectLeft, rectRight);
		GrayF32 disparity = ExampleStereoDisparity.denseDisparitySubpixel(
				rectLeft, rectRight, 3, disparityMin, disparityRange);

		// Remove speckle and smooth the disparity image. Typically this results in a less chaotic 3D model
		var configSpeckle = new ConfigSpeckleFilter();
		configSpeckle.similarTol = 1.0f; // Two pixels are connected if their disparity is this similar
		configSpeckle.maximumArea.setFixed(200); // probably the most important parameter, speckle size
		DisparitySmoother<GrayU8, GrayF32> smoother =
				FactoryStereoDisparity.removeSpeckle(configSpeckle, GrayF32.class);

		smoother.process(rectLeft, disparity, disparityRange);

		// Put disparity parameters into a format that the meshing algorithm can understand
		var parameters = new DisparityParameters();
		parameters.disparityRange = disparityRange;
		parameters.disparityMin = disparityMin;
		PerspectiveOps.matrixToPinhole(rectifier.getCalibrationMatrix(), rectLeft.width, rectLeft.height, parameters.pinhole);
		parameters.baseline = param.getBaseline()/10;

		// Convert the disparity image into a polygon mesh
		var alg = new DepthImageToMeshGridSample();
		alg.processDisparity(parameters, disparity, /* max disparity jump */ 2);
		VertexMesh mesh = alg.getMesh();

		// Specify the color of each vertex
		var colors = new DogArray_I32(mesh.vertexes.size());
		DogArray<Point2D_F64> pixels = alg.getVertexPixels();
		for (int i = 0; i < pixels.size; i++) {
			Point2D_F64 p = pixels.get(i);
			int v = rectLeft.get((int)p.x, (int)p.y);
			colors.add(v << 16 | v << 8 | v);

		// Save results. Display using a 3rd party application
		try (OutputStream out = new FileOutputStream("mesh.ply")) {
			PointCloudIO.save3D(PointCloudIO.Format.PLY, mesh, colors, out);
		} catch (IOException e) {
			throw new RuntimeException(e);