cv::stereoRectify(Camera_Intri_Left, Camera_Distcoff_Left, Camera_Intri_Right, Camera_Distcoff_Right, size, R, T, R1, R2, P1, P2, Q);
时间: 2024-05-21 13:15:44 浏览: 12
这是 OpenCV 中用于立体校正的函数。它需要输入左右相机的内参矩阵、畸变系数、图像尺寸、旋转矩阵和平移向量,以及输出的校正后的旋转矩阵、投影矩阵和深度映射矩阵。
立体校正是立体视觉中的一个重要步骤,它可以将左右相机的图像进行校正,使得它们的极线都是水平的,从而方便后续的处理。校正后的图像可以通过 remap 函数进行处理。
相关问题
cv::Mat camera_velodyne_rotation = rotation_matrix.t();
`cv::Mat camera_velodyne_rotation` 是一个变量,它是通过 `rotation_matrix` 的转置获得的。在 OpenCV 中,`cv::Mat` 是一个用于存储图像或矩阵数据的类。`rotation_matrix` 是一个旋转矩阵,通过对其进行转置操作 `t()`,可以得到 `camera_velodyne_rotation`。这个操作用于将 `rotation_matrix` 从原始坐标系转换到相机坐标系。
cv::SVD::V_T
cv::SVD::V_T is a member function of the cv::SVD class in OpenCV library. It returns the transpose of the matrix of right singular vectors of the input matrix. The right singular vectors are the eigenvectors of the transpose of the input matrix multiplied by the input matrix. The transpose of the right singular vectors matrix is also known as the matrix of left singular vectors.
In other words, if we have a matrix A, and we perform the Singular Value Decomposition (SVD) on it: A=U*S*V_T, then cv::SVD::V_T returns the matrix of right singular vectors V_T.
Syntax:
cv::Mat cv::SVD::V_T
Returns:
A cv::Mat object representing the transpose of the matrix of right singular vectors of the input matrix.
Example:
```
cv::Mat A = (cv::Mat_<double>(3,3) << 1, 2, 3, 4, 5, 6, 7, 8, 9);
cv::SVD svd(A);
cv::Mat V_T = svd.vt;
```
This code snippet calculates the SVD of a 3x3 matrix A and returns the transpose of the right singular vectors matrix in V_T.
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