在opencv python中分解同构矩阵 [英] Decompose Homography matrix in opencv python

问题描述

H = K [R | t] 其中H(3 * 3)是单应矩阵，R是旋转矩阵，K是摄像机固有参数矩阵，t是平移矢量.

H = K[R|t] where H (3*3) is homographic matrix, R is Rotation matrix, K is matrix of camera's intrinsic parameters and t is translation vector.

我已经使用国际象棋棋盘图案计算了K，如下所示:

I have calculated K using chess board pattern as follows

ret, K, dist, rvecs, tvecs = cv2.calibrateCamera(objpoints, imgpoints, chess_gray.shape[::-1],None,None)

Homograpy矩阵H的计算方式为

Homograpy matrix H is calculated as

pts_src = np.float32(pts_src)
pts_dst = np.float32(pts_dst)
H, status = cv2.findHomography(pts_src, pts_dst)

如何使用分解H和K中的R和t

How to decompose R and t from H and K using

cv2.decomposeHomograpyMat(H,K,....)

如何编写上述功能的其他输入和输出?

How to write other inputs and outputs of above functions?

推荐答案

假设H为单应矩阵，K为摄像机矩阵，则Python代码为:

Assuming H as homography matrix and K as camera matrix the Python code is:

num, Rs, Ts, Ns  = cv2.decomposeHomographyMat(H, K)

num 个可能的解决方案将被返回.

num possible solutions will be returned.

Rs包含旋转矩阵的列表.
Ts包含翻译向量的列表.
Ns包含平面法线向量的列表.

Rs contains a list of the rotation matrix.
Ts contains a list of the translation vector.
Ns contains a list of the normal vector of the plane.

有关更多信息，请查看官方文档:
OpenCV 3.4-decomposeHomographyMat()

For further informations take a look into the official documentation:
OpenCV 3.4 - decomposeHomographyMat()

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