public class ArucoDetector extends Algorithm
Modifier | Constructor and Description |
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ArucoDetector()
Basic ArucoDetector constructor
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ArucoDetector(Dictionary dictionary)
Basic ArucoDetector constructor
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ArucoDetector(Dictionary dictionary,
DetectorParameters detectorParams)
Basic ArucoDetector constructor
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ArucoDetector(Dictionary dictionary,
DetectorParameters detectorParams,
RefineParameters refineParams)
Basic ArucoDetector constructor
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protected |
ArucoDetector(long addr) |
Modifier and Type | Method and Description |
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static ArucoDetector |
__fromPtr__(long addr) |
void |
detectMarkers(Mat image,
List<Mat> corners,
Mat ids)
Basic marker detection
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void |
detectMarkers(Mat image,
List<Mat> corners,
Mat ids,
List<Mat> rejectedImgPoints)
Basic marker detection
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protected void |
finalize() |
DetectorParameters |
getDetectorParameters() |
Dictionary |
getDictionary() |
RefineParameters |
getRefineParameters() |
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
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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
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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
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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
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void |
setDetectorParameters(DetectorParameters detectorParameters) |
void |
setDictionary(Dictionary dictionary) |
void |
setRefineParameters(RefineParameters refineParameters) |
clear, empty, getDefaultName, getNativeObjAddr, save
protected ArucoDetector(long addr)
public ArucoDetector(Dictionary dictionary, DetectorParameters detectorParams, RefineParameters refineParams)
dictionary
- indicates the type of markers that will be searcheddetectorParams
- marker detection parametersrefineParams
- marker refine detection parameterspublic ArucoDetector(Dictionary dictionary, DetectorParameters detectorParams)
dictionary
- indicates the type of markers that will be searcheddetectorParams
- marker detection parameterspublic ArucoDetector(Dictionary dictionary)
dictionary
- indicates the type of markers that will be searchedpublic ArucoDetector()
public static ArucoDetector __fromPtr__(long addr)
public void detectMarkers(Mat image, List<Mat> corners, Mat ids, List<Mat> rejectedImgPoints)
image
- input imagecorners
- 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, estimatePoseBoardpublic void detectMarkers(Mat image, List<Mat> corners, Mat ids)
image
- input imagecorners
- 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, estimatePoseBoardpublic void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs, Mat recoveredIdxs)
image
- input imageboard
- 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 elementsrecoveredIdxs
- 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.public void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix, Mat distCoeffs)
image
- input imageboard
- 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.public void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners, Mat cameraMatrix)
image
- input imageboard
- 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.public void refineDetectedMarkers(Mat image, Board board, List<Mat> detectedCorners, Mat detectedIds, List<Mat> rejectedCorners)
image
- input imageboard
- 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.public Dictionary getDictionary()
public void setDictionary(Dictionary dictionary)
public DetectorParameters getDetectorParameters()
public void setDetectorParameters(DetectorParameters detectorParameters)
public RefineParameters getRefineParameters()
public void setRefineParameters(RefineParameters refineParameters)
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