Difference between revisions of "Example Rectification Calibrated"
From BoofCV
Jump to navigationJump to searchm |
m |
||
Line 8: | Line 8: | ||
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. | 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: [https://github.com/lessthanoptimal/BoofCV/blob/v0. | Example File: [https://github.com/lessthanoptimal/BoofCV/blob/v0.38/examples/src/main/java/boofcv/examples/stereo/ExampleRectifyCalibratedStereo.java ExampleRectifyCalibratedStereo.java] | ||
Concepts: | Concepts: |
Revision as of 12:10, 12 July 2021
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
Concepts:
- Stereo Rectification
- Stereo Vision
Related Examples:
Example Code
/**
* Shows how to rectify a pair of stereo images with known intrinsic parameters and stereo baseline. When you
* rectify a stereo pair you are applying a transform that removes lens distortion and "rotates" the views
* such that they are parallel to each other, facilitating stereo processing.
*
* The example code does the following:
* <lo>
* <li>Load stereo extrinsic and intrinsic parameters from a file along with a pair of images.</li>
* <li>Undistort and rectify images. This provides one rectification matrix for each image along with a new
* camera calibration matrix.</li>
* <li>The original rectification does not try to maximize view area, however it can be adjusted.</li>
* <li>After rectification is finished the results are displayed.</li>
* </lo>
*
* Note that the y-axis in left and right images align after rectification. You can click in the images to draw a line
* that makes this easy to see. The curved image birder is an artifact of lens distortion being removed.
*
* @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.convertFromPlanar(origLeft, null, true, GrayF32.class);
Planar<GrayF32> distRight =
ConvertBufferedImage.convertFromPlanar(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
DMatrixRMaj K1 = PerspectiveOps.pinholeToMatrix(param.getLeft(), (DMatrixRMaj)null);
DMatrixRMaj K2 = PerspectiveOps.pinholeToMatrix(param.getRight(), (DMatrixRMaj)null);
rectifyAlg.process(K1, new Se3_F64(), K2, leftToRight);
// rectification matrix for each image
DMatrixRMaj rect1 = rectifyAlg.getUndistToRectPixels1();
DMatrixRMaj rect2 = rectifyAlg.getUndistToRectPixels2();
// New calibration matrix,
// Both cameras have the same one after rectification.
DMatrixRMaj rectK = rectifyAlg.getCalibrationMatrix();
// Adjust the rectification to make the view area more useful
RectifyImageOps.fullViewLeft(param.left, rect1, rect2, rectK, null);
// RectifyImageOps.allInsideLeft(param.left, rect1, rect2, rectK, null);
// undistorted and rectify images
FMatrixRMaj rect1_F32 = new FMatrixRMaj(3, 3); // TODO simplify code some how
FMatrixRMaj rect2_F32 = new FMatrixRMaj(3, 3);
ConvertMatrixData.convert(rect1, rect1_F32);
ConvertMatrixData.convert(rect2, rect2_F32);
ImageDistort rectifyImageLeft =
RectifyDistortImageOps.rectifyImage(param.getLeft(), rect1_F32, BorderType.SKIP, distLeft.getImageType());
ImageDistort rectifyImageRight =
RectifyDistortImageOps.rectifyImage(param.getRight(), rect2_F32, BorderType.SKIP, distRight.getImageType());
rectifyImageLeft.apply(distLeft, rectLeft);
rectifyImageRight.apply(distRight, rectRight);
// 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);
}
}