Package org.opencv.objdetect

Class ArucoDetector

java.lang.Object
org.opencv.core.Algorithm
org.opencv.objdetect.ArucoDetector
public class ArucoDetector
extends Algorithm
The main functionality of ArucoDetector class is detection of markers in an image with detectMarkers() method. After detecting some markers in the image, you can try to find undetected markers from this dictionary with refineDetectedMarkers() method. SEE: DetectorParameters, RefineParameters

  • Constructor Details

  • Method Details

    • __fromPtr__

      public static ArucoDetector __fromPtr__​(long addr)

    • detectMarkers

      public void detectMarkers​(Mat image, List<Mat> corners, Mat ids, List<Mat> rejectedImgPoints)
      Basic marker detection
      Parameters:
      image - input image
      corners - vector of detected marker corners. For each marker, its four corners are provided, (e.g std::vector<std::vector<cv::Point2f> > ). For N detected markers, the dimensions of this array is Nx4. The order of the corners is clockwise.
      ids - vector of identifiers of the detected markers. The identifier is of type int (e.g. std::vector<int>). For N detected markers, the size of ids is also N. The identifiers have the same order than the markers in the imgPoints array.
      rejectedImgPoints - contains the imgPoints of those squares whose inner code has not a correct codification. Useful for debugging purposes. Performs marker detection in the input image. Only markers included in the specific dictionary are searched. For each detected marker, it returns the 2D position of its corner in the image and its corresponding identifier. Note that this function does not perform pose estimation. Note: The function does not correct lens distortion or takes it into account. It's recommended to undistort input image with corresponding camera model, if camera parameters are known SEE: undistort, estimatePoseSingleMarkers, estimatePoseBoard

    • detectMarkers

      public void detectMarkers​(Mat image, List<Mat> corners, Mat ids)
      Basic marker detection
      Parameters:
      image - input image
      corners - vector of detected marker corners. For each marker, its four corners are provided, (e.g std::vector<std::vector<cv::Point2f> > ). For N detected markers, the dimensions of this array is Nx4. The order of the corners is clockwise.
      ids - vector of identifiers of the detected markers. The identifier is of type int (e.g. std::vector<int>). For N detected markers, the size of ids is also N. The identifiers have the same order than the markers in the imgPoints array. correct codification. Useful for debugging purposes. Performs marker detection in the input image. Only markers included in the specific dictionary are searched. For each detected marker, it returns the 2D position of its corner in the image and its corresponding identifier. Note that this function does not perform pose estimation. Note: The function does not correct lens distortion or takes it into account. It's recommended to undistort input image with corresponding camera model, if camera parameters are known SEE: undistort, estimatePoseSingleMarkers, estimatePoseBoard

    • refineDetectedMarkers

      public void refineDetectedMarkers​(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, Mat recoveredIdxs)
      Refine not detected markers based on the already detected and the board layout
      Parameters:
      image - input image
      board - layout of markers in the board.
      detectedCorners - vector of already detected marker corners.
      detectedIds - vector of already detected marker identifiers.
      rejectedCorners - vector of rejected candidates during the marker detection process.
      cameraMatrix - optional input 3x3 floating-point camera matrix \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\)
      distCoeffs - optional vector of distortion coefficients \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements
      recoveredIdxs - Optional array to returns the indexes of the recovered candidates in the original rejectedCorners array. This function tries to find markers that were not detected in the basic detecMarkers function. First, based on the current detected marker and the board layout, the function interpolates the position of the missing markers. Then it tries to find correspondence between the reprojected markers and the rejected candidates based on the minRepDistance and errorCorrectionRate parameters. If camera parameters and distortion coefficients are provided, missing markers are reprojected using projectPoint function. If not, missing marker projections are interpolated using global homography, and all the marker corners in the board must have the same Z coordinate.

    • refineDetectedMarkers

      public void refineDetectedMarkers​(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs)
      Refine not detected markers based on the already detected and the board layout
      Parameters:
      image - input image
      board - layout of markers in the board.
      detectedCorners - vector of already detected marker corners.
      detectedIds - vector of already detected marker identifiers.
      rejectedCorners - vector of rejected candidates during the marker detection process.
      cameraMatrix - optional input 3x3 floating-point camera matrix \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\)
      distCoeffs - optional vector of distortion coefficients \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements original rejectedCorners array. This function tries to find markers that were not detected in the basic detecMarkers function. First, based on the current detected marker and the board layout, the function interpolates the position of the missing markers. Then it tries to find correspondence between the reprojected markers and the rejected candidates based on the minRepDistance and errorCorrectionRate parameters. If camera parameters and distortion coefficients are provided, missing markers are reprojected using projectPoint function. If not, missing marker projections are interpolated using global homography, and all the marker corners in the board must have the same Z coordinate.

    • refineDetectedMarkers

      public void refineDetectedMarkers​(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix)
      Refine not detected markers based on the already detected and the board layout
      Parameters:
      image - input image
      board - layout of markers in the board.
      detectedCorners - vector of already detected marker corners.
      detectedIds - vector of already detected marker identifiers.
      rejectedCorners - vector of rejected candidates during the marker detection process.
      cameraMatrix - optional input 3x3 floating-point camera matrix \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements original rejectedCorners array. This function tries to find markers that were not detected in the basic detecMarkers function. First, based on the current detected marker and the board layout, the function interpolates the position of the missing markers. Then it tries to find correspondence between the reprojected markers and the rejected candidates based on the minRepDistance and errorCorrectionRate parameters. If camera parameters and distortion coefficients are provided, missing markers are reprojected using projectPoint function. If not, missing marker projections are interpolated using global homography, and all the marker corners in the board must have the same Z coordinate.

    • refineDetectedMarkers

      public void refineDetectedMarkers​(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners)
      Refine not detected markers based on the already detected and the board layout
      Parameters:
      image - input image
      board - layout of markers in the board.
      detectedCorners - vector of already detected marker corners.
      detectedIds - vector of already detected marker identifiers.
      rejectedCorners - vector of rejected candidates during the marker detection process. \(A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\) \((k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\) of 4, 5, 8 or 12 elements original rejectedCorners array. This function tries to find markers that were not detected in the basic detecMarkers function. First, based on the current detected marker and the board layout, the function interpolates the position of the missing markers. Then it tries to find correspondence between the reprojected markers and the rejected candidates based on the minRepDistance and errorCorrectionRate parameters. If camera parameters and distortion coefficients are provided, missing markers are reprojected using projectPoint function. If not, missing marker projections are interpolated using global homography, and all the marker corners in the board must have the same Z coordinate.

    • getDictionary

      public Dictionary getDictionary()

    • setDictionary

      public void setDictionary​(Dictionary dictionary)

    • getDetectorParameters

      public DetectorParameters getDetectorParameters()

    • setDetectorParameters

      public void setDetectorParameters​(DetectorParameters detectorParameters)

    • getRefineParameters

      public RefineParameters getRefineParameters()

    • setRefineParameters

      public void setRefineParameters​(RefineParameters refineParameters)

    • finalize

      protected void finalize() throws Throwable
      Overrides:
      finalize in class Algorithm
      Throws:
      Throwable