Example Calibrate Planar Fisheye

• 

  Detected Calibration Target in a Fisheye Camera.

This example demonstrates how to compute the intrinsic camera parameters for a fisheye camera lens. Fisheye lenses exhibit significantly more distortion than regular lenses with a more narrow field of view. Its not unusual for a fisheye lens to have a FOV of 185 degrees. The calibration process is very similar to regular cameras. A planar calibration target is shown at different angles across the entire field of view. The main difference is the camera model.

Example File: ExampleCalibrateFisheye.java

Calibration Tutorial: Wikipage

Concepts:

• Camera calibration
• Fisheye Lens distortion
• Intrinsic parameters

Relevant Videos:

• YouTube Video

Related Examples:

• Calibrate Regular Lenses

Example Code

/**
 * Example of how to calibrate a single (monocular) fisheye camera using a high level interface. This example
 * for the most part follows the same routine as {@link ExampleCalibrateMonocular}. Fisheye cameras tend to require
 * more images to properly calibrate. Often people will use larger calibration targets too that are easier to
 * see at a distance and cover more of the fisheye's camera large FOV.
 *
 * @author Peter Abeles
 * @see CalibrateMonoPlanar
 */
public class ExampleCalibrateFisheye {
	public static void main( String[] args ) {
		DetectSingleFiducialCalibration detector;

		// Circle based calibration targets are not recommended because the sever lens distortion will change
		// the apparent location of tangent points.

		// Square Grid example
//		detector = FactoryFiducialCalibration.squareGrid(null, new ConfigGridDimen(/*rows*/ 4, /*cols*/ 3, /*size*/ 30, /*space*/ 30));
//		images = UtilIO.listAll(UtilIO.pathExample("calibration/fisheye/square_grid"));

//		 Chessboard Example
		detector = FactoryFiducialCalibration.chessboardX(null, new ConfigGridDimen(/*rows*/7, /*cols*/5, /*size*/30));
		List<String> images = UtilIO.listAll(UtilIO.pathExample("calibration/fisheye/chessboard"));

		// Declare and setup the calibration algorithm
		var calibrator = new CalibrateMonoPlanar();

		// Specify the camera model to use. Here are a few examples.
		//
		calibrator.configureUniversalOmni( /*zeroSkew*/ true, /*radial*/ 2, /*tangential*/ false);
		// it's also possible to fix the mirror offset parameter
		// 0 = pinhole camera. 1 = fisheye
//		calibrationAlg.configureUniversalOmni( /*zeroSkew*/ true, /*radial*/ 2, /*tangential*/ false, /*offset*/ 1.0);
		// Another popular model is Kannala-Brandt. Most people just use the symmetric terms.
//		calibrationAlg.configureKannalaBrandt( /*zeroSkew*/ true, /*symmetric*/ 5, /*asymmetric*/ 0);

		var usedImages = new ArrayList<String>();
		for (String n : images) {
			BufferedImage input = UtilImageIO.loadImage(n);
			if (input == null)
				continue;
			GrayF32 image = ConvertBufferedImage.convertFrom(input, (GrayF32)null);
			if (detector.process(image)) {
				// Need to tell it the image shape and the layout once
				if (usedImages.isEmpty())
					calibrator.initialize(image.getWidth(), image.getHeight(), List.of(detector.getLayout()));
				calibrator.addImage(detector.getDetectedPoints().copy());
				usedImages.add(n);
			} else {
				System.err.println("Failed to detect target in " + n);
			}
		}
		// process and compute intrinsic parameters
		CameraModel intrinsic = calibrator.process();

		// save results to a file and print out
		CalibrationIO.save(intrinsic, "fisheye.yaml");

		System.out.println(calibrator.computeQualityText(usedImages));
		System.out.println();
		System.out.println("--- Intrinsic Parameters ---");
		System.out.println();
		intrinsic.print();
	}
}