The CameraCalibration type exposes the following methods.
Methods
 Public Protected | Instance Static | Declared Inherited | XNA Framework Only .NET Compact Framework Only |
| Member | Description | |
|---|---|---|
  | CalibrateCamera(array<array<MCvPoint3D32f>[]()[][]>[]()[][], array<array<PointF>[]()[][]>[]()[][], Size, IntrinsicCameraParameters, CALIB_TYPE, array<ExtrinsicCameraParameters>[]()[][]%) |
Estimates intrinsic camera parameters and extrinsic parameters for each of the views
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| DrawChessboardCorners(Image<(Of <<'(Gray, Byte>)>>), Size, array<PointF>[]()[][], Boolean) |
Draws the individual chessboard corners detected (as red circles) in case if the board was not found (patternWasFound== false) or the colored corners connected with lines when the board was found (patternWasFound == true).
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| FindChessboardCorners(Image<(Of <<'(Gray, Byte>)>>), Size, CALIB_CB_TYPE, array<PointF>[]()[][]%) |
attempts to determine whether the input image is a view of the chessboard pattern and locate internal chessboard corners
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| FindExtrinsicCameraParams2(array<MCvPoint3D32f>[]()[][], array<PointF>[]()[][], IntrinsicCameraParameters) |
Estimates extrinsic camera parameters using known intrinsic parameters and extrinsic parameters for each view. The coordinates of 3D object points and their correspondent 2D projections must be specified. This function also minimizes back-projection error.
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| FindHomography(array<PointF>[]()[][], array<PointF>[]()[][], HOMOGRAPHY_METHOD, Double) |
Finds perspective transformation H=||h_ij|| between the source and the destination planes
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| FindHomography(Matrix<(Of <<'(Single>)>>), Matrix<(Of <<'(Single>)>>), HOMOGRAPHY_METHOD, Double) |
Use the specific method to find perspective transformation H=||h_ij|| between the source and the destination planes
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| GetAffineTransform(array<PointF>[]()[][], array<PointF>[]()[][]) |
Calculates the matrix of an affine transform such that:
(x'_i,y'_i)^T=map_matrix (x_i,y_i,1)^T
where dst(i)=(x'_i,y'_i), src(i)=(x_i,y_i), i=0..2.
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| GetPerspectiveTransform(array<PointF>[]()[][], array<PointF>[]()[][]) |
calculates matrix of perspective transform such that:
(t_i x'_i,t_i y'_i,t_i)^T=map_matrix (x_i,y_i,1)^T
where dst(i)=(x'_i,y'_i), src(i)=(x_i,y_i), i=0..3.
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| ProjectPoints(array<MCvPoint3D32f>[]()[][], ExtrinsicCameraParameters, IntrinsicCameraParameters, array<Matrix<(Of <<'(Single>)>>)>[]()[][]) |
Computes projections of 3D points to the image plane given intrinsic and extrinsic camera parameters.
Optionally, the function computes jacobians - matrices of partial derivatives of image points as functions of all the input parameters w.r.t. the particular parameters, intrinsic and/or extrinsic.
The jacobians are used during the global optimization in cvCalibrateCamera2 and cvFindExtrinsicCameraParams2.
The function itself is also used to compute back-projection error for with current intrinsic and extrinsic parameters.
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| StereoCalibrate(array<array<MCvPoint3D32f>[]()[][]>[]()[][], array<array<PointF>[]()[][]>[]()[][], array<array<PointF>[]()[][]>[]()[][], IntrinsicCameraParameters, IntrinsicCameraParameters, Size, CALIB_TYPE, MCvTermCriteria, ExtrinsicCameraParameters%, Matrix<(Of <<'(Double>)>>)%, Matrix<(Of <<'(Double>)>>)%) |
Estimates transformation between the 2 cameras making a stereo pair. If we have a stereo camera, where the relative position and orientatation of the 2 cameras is fixed, and if we computed poses of an object relative to the fist camera and to the second camera, (R1, T1) and (R2, T2), respectively (that can be done with cvFindExtrinsicCameraParams2), obviously, those poses will relate to each other, i.e. given (R1, T1) it should be possible to compute (R2, T2) - we only need to know the position and orientation of the 2nd camera relative to the 1st camera. That's what the described function does. It computes (R, T) such that:
R2=R*R1,
T2=R*T1 + T
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See Also
