Example Rectification Calibrated

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Stereo rectification is the process of distorting an image such that the epipoles of both images are at infinity. If the epipoles are at infinity along the x-axis, then corresponding features must lie along the same y-coordinates. Using knowledge that correspondence feature's have the same y-coordinate allows for quick searches. Many stereo vision algorithm rely on rectification. The example below demonstrates rectification for a calibrated stereo pair. Note that after calibration the new camera view has a different set of intrinsic parameters.

Example File: ExampleRectifyCalibratedStereo.java


  • Stereo Rectification
  • Stereo Vision

Related Examples:

Example Code

 * <p>
 * Shows how to rectify a pair of stereo images with known intrinsic parameters and stereo baseline.
 * The example code does the following:<br>
 * 1) Load stereo parameters from XML file with a pair of images.<br>
 * 2) Undistort and rectify images..  This provides one rectification matrix
 * for each image along with a new camera calibration matrix.<br>
 * 3) The original rectification does not try to maximize view area, however it can be adjusted.
 * 4)After rectification is finished the results are displayed.<br>
 * </p>
 * <p>
 * Note that the y-axis in left and right images align after rectification.  The curved image edge
 * is an artifact of lens distortion being removed.
 * </p>
 * @author Peter Abeles
public class ExampleRectifyCalibratedStereo {
	public static void main( String args[] ) {
		String dir = UtilIO.pathExample("calibration/stereo/Bumblebee2_Chess/");
		StereoParameters param = CalibrationIO.load(new File(dir , "stereo.yaml"));
		// load images
		BufferedImage origLeft = UtilImageIO.loadImage(dir,"left05.jpg");
		BufferedImage origRight = UtilImageIO.loadImage(dir,"right05.jpg");
		// distorted images
		Planar<GrayF32> distLeft =
				ConvertBufferedImage.convertFromMulti(origLeft, null,true, GrayF32.class);
		Planar<GrayF32> distRight =
				ConvertBufferedImage.convertFromMulti(origRight, null,true, GrayF32.class);
		// storage for undistorted + rectified images
		Planar<GrayF32> rectLeft = distLeft.createSameShape();
		Planar<GrayF32> rectRight = distRight.createSameShape();
		// Compute rectification
		RectifyCalibrated rectifyAlg = RectifyImageOps.createCalibrated();
		Se3_F64 leftToRight = param.getRightToLeft().invert(null);
		// original camera calibration matrices
		DenseMatrix64F K1 = PerspectiveOps.calibrationMatrix(param.getLeft(), null);
		DenseMatrix64F K2 = PerspectiveOps.calibrationMatrix(param.getRight(), null);
		rectifyAlg.process(K1,new Se3_F64(),K2,leftToRight);
		// rectification matrix for each image
		DenseMatrix64F rect1 = rectifyAlg.getRect1();
		DenseMatrix64F rect2 = rectifyAlg.getRect2();
		// New calibration matrix,
		// Both cameras have the same one after rectification.
		DenseMatrix64F rectK = rectifyAlg.getCalibrationMatrix();
		// Adjust the rectification to make the view area more useful
		RectifyImageOps.fullViewLeft(param.left, rect1, rect2, rectK);
//		RectifyImageOps.allInsideLeft(param.left, leftHanded, rect1, rect2, rectK);
		// undistorted and rectify images
		ImageDistort rectifyImageLeft =
				RectifyImageOps.rectifyImage(param.getLeft(), rect1, BorderType.SKIP, distLeft.getImageType());
		ImageDistort rectifyImageRight =
				RectifyImageOps.rectifyImage(param.getRight(), rect2, BorderType.SKIP, distRight.getImageType());
		// convert for output
		BufferedImage outLeft = ConvertBufferedImage.convertTo(rectLeft,null,true);
		BufferedImage outRight = ConvertBufferedImage.convertTo(rectRight, null,true);
		// show results and draw a horizontal line where the user clicks to see rectification easier
		ListDisplayPanel panel = new ListDisplayPanel();
		panel.addItem(new RectifiedPairPanel(true, origLeft, origRight), "Original");
		panel.addItem(new RectifiedPairPanel(true, outLeft, outRight), "Rectified");
		ShowImages.showWindow(panel,"Stereo Rectification Calibrated",true);