Difference between revisions of "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. | 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/v0.33/examples/src/main/java/boofcv/examples/stereo/ExampleRectifyCalibratedStereo.java ExampleRectifyCalibratedStereo.java] | ||
Concepts: | Concepts: | ||
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Related Examples: | Related Examples: | ||
* [[Example_Calibrate_Planar_Stereo| Stereo Camera Calibration]] | * [[Example_Calibrate_Planar_Stereo| Stereo Camera Calibration]] | ||
* [[Example_Remove_Lens_Distortion| Removing Lens Distortion]] | * [[Example_Remove_Lens_Distortion| Removing Lens Distortion]] |
Revision as of 07:04, 15 March 2019
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
/**
* <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.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.getRect1();
DMatrixRMaj rect2 = rectifyAlg.getRect2();
// 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);
// RectifyImageOps.allInsideLeft(param.left, leftHanded, rect1, rect2, rectK);
// 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 =
RectifyImageOps.rectifyImage(param.getLeft(), rect1_F32, BorderType.SKIP, distLeft.getImageType());
ImageDistort rectifyImageRight =
RectifyImageOps.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);
}
}