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opencv-wasm

stereoCalibrateExtended

Calibration and geometryfunctionOpenCV 5.0.0
import { stereoCalibrateExtended } from '@banou/opencv-wasm'

Use after await initOpenCV(). See the initialization and named imports guide.

ARGUMENTSobjectPoints, imagePoints1, imagePoints2, cameraMatrix1
FUNCTIONstereoCalibrateExtended
RETURN TYPEnumber
Call structure. A void return can still write to destination arguments. The parameter descriptions define inputs, outputs and ownership.

Calibrates a stereo camera set up. This function finds the intrinsic parameters for each of the two cameras and the extrinsic parameters between the two cameras.

stereoCalibrateExtended(objectPoints: MatVector, imagePoints1: MatVector, imagePoints2: MatVector, cameraMatrix1: Mat, distCoeffs1: Mat, cameraMatrix2: Mat, distCoeffs2: Mat, imageSize: Size, R: Mat, T: Mat, E: Mat, F: Mat, rvecs: MatVector, tvecs: MatVector, perViewErrors: Mat, flags: number, criteria: TermCriteria): number;
3 available overloads
stereoCalibrateExtended(objectPoints: MatVector, imagePoints1: MatVector, imagePoints2: MatVector, cameraMatrix1: Mat, distCoeffs1: Mat, cameraMatrix2: Mat, distCoeffs2: Mat, imageSize: Size, R: Mat, T: Mat, E: Mat, F: Mat, rvecs: MatVector, tvecs: MatVector, perViewErrors: Mat): number;
stereoCalibrateExtended(objectPoints: MatVector, imagePoints1: MatVector, imagePoints2: MatVector, cameraMatrix1: Mat, distCoeffs1: Mat, cameraMatrix2: Mat, distCoeffs2: Mat, imageSize: Size, R: Mat, T: Mat, E: Mat, F: Mat, rvecs: MatVector, tvecs: MatVector, perViewErrors: Mat, flags: number): number;
stereoCalibrateExtended(objectPoints: MatVector, imagePoints1: MatVector, imagePoints2: MatVector, cameraMatrix1: Mat, distCoeffs1: Mat, cameraMatrix2: Mat, distCoeffs2: Mat, imageSize: Size, R: Mat, T: Mat, E: Mat, F: Mat, rvecs: MatVector, tvecs: MatVector, perViewErrors: Mat, flags: number, criteria: TermCriteria): number;
objectPoints

Vector of vectors of the calibration pattern points. The same structure as in calibrateCamera. For each pattern view, both cameras need to see the same object points. Therefore, objectPoints.size(), imagePoints1.size(), and imagePoints2.size() need to be equal as well as objectPoints[i].size(), imagePoints1[i].size(), and imagePoints2[i].size() need to be equal for each i.

imagePoints1

Vector of vectors of the projections of the calibration pattern points, observed by the first camera. The same structure as in calibrateCamera.

imagePoints2

Vector of vectors of the projections of the calibration pattern points, observed by the second camera. The same structure as in calibrateCamera.

cameraMatrix1

Input/output value, modified by the native operation. Input/output camera intrinsic matrix for the first camera, the same as in calibrateCamera. Furthermore, for the stereo case, additional flags may be used, see below.

distCoeffs1

Input/output value, modified by the native operation. Input/output vector of distortion coefficients, the same as in calibrateCamera.

cameraMatrix2

Input/output value, modified by the native operation. Input/output second camera intrinsic matrix for the second camera. See description for cameraMatrix1.

distCoeffs2

Input/output value, modified by the native operation. Input/output lens distortion coefficients for the second camera. See description for distCoeffs1.

imageSize

Size of the image used only to initialize the camera intrinsic matrices.

R

Input/output value, modified by the native operation. Output rotation matrix. Together with the translation vector T, this matrix brings points given in the first camera's coordinate system to points in the second camera's coordinate system. In more technical terms, the tuple of R and T performs a change of basis from the first camera's coordinate system to the second camera's coordinate system. Due to its duality, this tuple is equivalent to the position of the first camera with respect to the second camera coordinate system.

T

Input/output value, modified by the native operation. Output translation vector, see description above.

E

Output destination, filled by the native operation. Output essential matrix.

F

Output destination, filled by the native operation. Output fundamental matrix.

rvecs

Output destination, filled by the native operation. Output vector of rotation vectors ( Rodrigues ) estimated for each pattern view in the coordinate system of the first camera of the stereo pair (e.g. std::vectorcv::Mat). More in detail, each i-th rotation vector together with the corresponding i-th translation vector (see the next output parameter description) brings the calibration pattern from the object coordinate space (in which object points are specified) to the camera coordinate space of the first camera of the stereo pair. In more technical terms, the tuple of the i-th rotation and translation vector performs a change of basis from object coordinate space to camera coordinate space of the first camera of the stereo pair.

tvecs

Output destination, filled by the native operation. Output vector of translation vectors estimated for each pattern view, see parameter description of previous output parameter ( rvecs ).

perViewErrors

Output destination, filled by the native operation. Output vector of the RMS re-projection error estimated for each pattern view.

flags

Different flags that may be zero or a combination of the following values:

  • CALIB_FIX_INTRINSIC Fix cameraMatrix? and distCoeffs? so that only R, T, E, and F matrices are estimated.
  • CALIB_USE_INTRINSIC_GUESS Optimize some or all of the intrinsic parameters according to the specified flags. Initial values are provided by the user.
  • CALIB_USE_EXTRINSIC_GUESS R and T contain valid initial values that are optimized further. Otherwise R and T are initialized to the median value of the pattern views (each dimension separately).
  • CALIB_FIX_PRINCIPAL_POINT Fix the principal points during the optimization.
  • CALIB_FIX_FOCAL_LENGTH Fix f^{(j)}_x and f^{(j)}_y .
  • CALIB_FIX_ASPECT_RATIO Optimize f^{(j)}_y . Fix the ratio f^{(j)}_x/f^{(j)}_y .
  • CALIB_SAME_FOCAL_LENGTH Enforce f^{(0)}_x=f^{(1)}_x and f^{(0)}_y=f^{(1)}_y .
  • CALIB_ZERO_TANGENT_DIST Set tangential distortion coefficients for each camera to zeros and fix there.
  • CALIB_FIX_K1,..., CALIB_FIX_K6 Do not change the corresponding radial distortion coefficient during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
  • CALIB_RATIONAL_MODEL Enable coefficients k4, k5, and k6. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the rational model and return 8 coefficients. If the flag is not set, the function computes and returns only 5 distortion coefficients.
  • CALIB_THIN_PRISM_MODEL Coefficients s1, s2, s3 and s4 are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the thin prism model and return 12 coefficients. If the flag is not set, the function computes and returns only 5 distortion coefficients.
  • CALIB_FIX_S1_S2_S3_S4 The thin prism distortion coefficients are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
  • CALIB_TILTED_MODEL Coefficients tauX and tauY are enabled. To provide the backward compatibility, this extra flag should be explicitly specified to make the calibration function use the tilted sensor model and return 14 coefficients. If the flag is not set, the function computes and returns only 5 distortion coefficients.
  • CALIB_FIX_TAUX_TAUY The coefficients of the tilted sensor model are not changed during the optimization. If CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.
criteria

Termination criteria for the iterative optimization algorithm.

The function estimates the transformation between two cameras making a stereo pair. If one computes the poses of an object relative to the first camera and to the second camera, ( R_1,T_1 ) and (R_2,T_2), respectively, for a stereo camera where the relative position and orientation between the two cameras are fixed, then those poses definitely relate to each other. This means, if the relative position and orientation (R,T) of the two cameras is known, it is possible to compute (R_2,T_2) when (R_1,T_1) is given. This is what the described function does. It computes (R,T) such that:

R_2=R R_1

T_2=R T_1 + T.

Therefore, one can compute the coordinate representation of a 3D point for the second camera's coordinate system when given the point's coordinate representation in the first camera's coordinate system:

\begin{bmatrix}
X_2 \\
Y_2 \\
Z_2 \\
1
\end{bmatrix} = \begin{bmatrix}
R & T \\
0 & 1
\end{bmatrix} \begin{bmatrix}
X_1 \\
Y_1 \\
Z_1 \\
1
\end{bmatrix}.

Optionally, it computes the essential matrix E:

E= \vecthreethree{0}{-T_2}{T_1}{T_2}{0}{-T_0}{-T_1}{T_0}{0} R

where T_i are components of the translation vector T : T=[T_0, T_1, T_2]^T . And the function can also compute the fundamental matrix F:

F = cameraMatrix2^{-T}\cdot E \cdot cameraMatrix1^{-1}

Besides the stereo-related information, the function can also perform a full calibration of each of the two cameras. However, due to the high dimensionality of the parameter space and noise in the input data, the function can diverge from the correct solution. If the intrinsic parameters can be estimated with high accuracy for each of the cameras individually (for example, using #calibrateCamera ), you are recommended to do so and then pass CALIB_FIX_INTRINSIC flag to the function along with the computed intrinsic parameters. Otherwise, if all the parameters are estimated at once, it makes sense to restrict some parameters, for example, pass CALIB_SAME_FOCAL_LENGTH and CALIB_ZERO_TANGENT_DIST flags, which is usually a reasonable assumption.

Similarly to #calibrateCamera, the function minimizes the total re-projection error for all the points in all the available views from both cameras. The function returns the final value of the re-projection error.

Returns

The number result.

Upstream declaration ↗

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