仅使用径向畸变校准相机

Question

我正在尝试运行在 python 中使用 opencv 进行相机校准。我正在使用：

cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None,None)

而且它似乎适用于 5 个失真系数。但是，我想尝试运行它没有切向畸变并且可能只有 2 个径向畸变系数。这可能吗？

Answer 1

我找到了答案。

无切向畸变：

 ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None, 4,None,None,cv2.CALIB_ZERO_TANGENT_DIST,
                                                   criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 2e-16))

对于只有 2 个径向失真系数，文档似乎建议使用 4 而不是 5 作为系数的数量。这似乎不起作用。相反，我修复了 k3 参数：

ret, mtx, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, gray.shape[::-1],None, 4,None,None,cv2.CALIB_ZERO_TANGENT_DIST+cv2.CALIB_FIX_K3,
                                                   criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 2e-16))

Answer 2

The relevant documentation:

distCoeffs – Output vector of distortion coefficients $(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6 [, s_1, s_2, s_3, s_4[, \tau_x, \tau_y]]]])$ of 4, 5, or 8 elements.

CV_CALIB_USE_INTRINSIC_GUESS cameraMatrix contains valid initial values of fx, fy, cx, cy that are optimized further. Otherwise, (cx, cy) is initially set to the image center ( imageSize is used), and focal distances are computed in a least-squares fashion. Note, that if intrinsic parameters are known, there is no need to use this function just to estimate extrinsic parameters. Use solvePnP() instead.

CV_CALIB_FIX_K1,...,CV_CALIB_FIX_K6 The corresponding radial distortion coefficient is not changed during the optimization. If CV_CALIB_USE_INTRINSIC_GUESS is set, the coefficient from the supplied distCoeffs matrix is used. Otherwise, it is set to 0.

CV_CALIB_ZERO_TANGENT_DIST Tangential distortion coefficients $(p_1, p_2)$ are set to zeros and stay zero.

重要：在 Python 中，简历标志不要以 CV_ 开头。所以我会从现在开始删除它们。

文档的意思是：

如果你已经一个相机矩阵和畸变系数向量，你可以将它们作为初始值提供给校准，让它从那里猜测（使用 CALIB_USE_INTRINSIC_GUESS）。您可以使用 CALIB_FIX_K1,...,CALIB_FIX_K6 标志来提供初始失真向量并使其中的某些组件成为静态的（将始终是提供的值）。

但是： 如果您设置 CALIB_FIX_K1、CALIB_FIX_K2、CALIB_FIX_K3、CALIB_FIX_K4、CALIB_FIX_K5 或CALIB_FIX_K6 如果不给出初步估计，它们将被设置为零。

请注意，结果 distCoeffs 向量将为：[K1、K2、tangential1、tangential2、K3]。 OpenCV 只会在你用 CALIB_RATIONAL_MODEL.

明确要求时给你 K4、K5 或 K6

因此，如果您不需要切向畸变因子而只需要两个径向畸变因子，您可以提供 flags=CALIB_FIX_K3 + CALIB_ZERO_TANGENT_DIST。您不需要 distCoeffs 或将其作为 distCoeffs=None.

传递

success, mtx, distCoeffs, rvecs, tvecs = cv2.calibrateCamera(
        objectPoints, imagePoints, (width, height),
        flags=CALIB_FIX_K3 + CALIB_ZERO_TANGENT_DIST)

print(distCoeffs)

这将导致像这样的失真向量：

[ 0.10509459 -0.31389323 0. 0. 0. ]

仅使用径向畸变校准相机

Calibrate Camera with only radial distortion

python

opencv

camera-calibration