Example Stereo Disparity 3D
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3D point cloud generated from disparity image. | Stereo Update Video |
An additional example for stereo disparity. This one shows you how to properly resize input images and convert the disparity image into a 3D point cloud.
Example Code:
Concepts:
- Stereo disparity
- Point clouds
Related Videos
Related Examples:
Example Code
/**
* Expanding upon ExampleStereoDisparity, this example demonstrates how to rescale an image for stereo processing and
* then compute its 3D point cloud. Images are often rescaled to improve speed and some times quality. Creating
* 3D point clouds from disparity images is easy and well documented in the literature, but there are some nuances
* to it.
*
* @author Peter Abeles
*/
public class ExampleStereoDisparity3D {
// Specifies the disparity values which will be considered
private static final int disparityMin = 15;
private static final int disparityRange = 60;
/**
* Given already computed rectified images and known stereo parameters, create a 3D cloud and visualize it
*/
public static JComponent computeAndShowCloud( StereoParameters param,
GrayU8 rectLeft,
RectifyCalibrated rectAlg, GrayF32 disparity ) {
// The point cloud will be in the left cameras reference frame
DMatrixRMaj rectK = rectAlg.getCalibrationMatrix();
DMatrixRMaj rectR = rectAlg.getRectifiedRotation();
// Put all the disparity parameters into one data structure
var disparityParameters = new DisparityParameters();
disparityParameters.baseline = param.getBaseline();
disparityParameters.disparityMin = disparityMin;
disparityParameters.disparityRange = disparityRange;
disparityParameters.rotateToRectified.setTo(rectR);
PerspectiveOps.matrixToPinhole(rectK, rectLeft.width, rectLeft.height, disparityParameters.pinhole);
// Iterate through each pixel in disparity image and compute its 3D coordinate
PointCloudViewer pcv = VisualizeData.createPointCloudViewer();
pcv.setTranslationStep(param.getBaseline()*0.1);
// Next create the 3D point cloud. The function below will handle conversion from disparity into
// XYZ, then transform from rectified into normal camera coordinate system. Feel free to glance at the
// source code to understand exactly what it's doing
MultiViewStereoOps.disparityToCloud(disparity, disparityParameters, null,
( pixX, pixY, x, y, z ) -> {
// look up the gray value. Then convert it into RGB
int v = rectLeft.unsafe_get(pixX, pixY);
pcv.addPoint(x, y, z, v << 16 | v << 8 | v);
});
// Configure the display
// pcv.setFog(true);
// pcv.setClipDistance(baseline*45);
// PeriodicColorizer colorizer = new TwoAxisRgbPlane.Z_XY(4.0);
// colorizer.setPeriod(baseline*5);
// pcv.setColorizer(colorizer); // sometimes pseudo color can be easier to view
pcv.setDotSize(1);
pcv.setCameraHFov(PerspectiveOps.computeHFov(param.left));
// pcv.setCameraToWorld(cameraToWorld);
JComponent viewer = pcv.getComponent();
viewer.setPreferredSize(new Dimension(600, 600*param.left.height/param.left.width));
return viewer;
}
public static void main( String[] args ) {
// ------------- Compute Stereo Correspondence
// Load camera images and stereo camera parameters
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, "chair01_left.jpg");
BufferedImage origRight = UtilImageIO.loadImage(imageDir, "chair01_right.jpg");
GrayU8 distLeft = ConvertBufferedImage.convertFrom(origLeft, (GrayU8)null);
GrayU8 distRight = ConvertBufferedImage.convertFrom(origRight, (GrayU8)null);
// rectify images and compute disparity
GrayU8 rectLeft = distLeft.createSameShape();
GrayU8 rectRight = distRight.createSameShape();
RectifyCalibrated rectAlg = ExampleStereoDisparity.rectify(distLeft, distRight, param, rectLeft, rectRight);
// GrayU8 disparity = ExampleStereoDisparity.denseDisparity(rectLeft, rectRight, 3,disparityMin, disparityRange);
GrayF32 disparity = ExampleStereoDisparity.denseDisparitySubpixel(
rectLeft, rectRight, 5, disparityMin, disparityRange);
// ------------- Convert disparity image into a 3D point cloud
JComponent viewer = computeAndShowCloud(param, rectLeft, rectAlg, disparity);
// display the results. Click and drag to change point cloud camera
BufferedImage visualized = VisualizeImageData.disparity(disparity, null, disparityRange, 0);
ShowImages.showWindow(visualized, "Disparity", true);
ShowImages.showWindow(viewer, "Point Cloud", true);
}
}