python写一个程序,把在左相机下的得到的16个世界坐标列表根据左右相机双目标定得到的外参转到右相机坐标系下
时间: 2023-06-17 08:07:02 浏览: 98
Python opencv相机标定实现原理及步骤详解
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假设左相机得到的16个世界坐标列表为`points3D_left`,左右相机的内参矩阵分别为`K_left`和`K_right`,左右相机的畸变系数分别为`dist_left`和`dist_right`,左右相机的旋转矩阵为`R`,平移向量为`t`。
首先,将左相机下的世界坐标转换为相机坐标系下的坐标:
```python
import cv2
import numpy as np
# 将16个世界坐标转换为相机坐标系下的坐标
points3D_left = np.array(points3D_left, dtype=np.float32)
points3D_left = np.hstack((points3D_left, np.ones((points3D_left.shape[0], 1), dtype=np.float32)))
R_inv = cv2.Rodrigues(R)[0] # 计算旋转矩阵的逆矩阵
t_inv = -R_inv.dot(t)
points3D_cam = R_inv.dot(points3D_left.T - t_inv).T
```
然后,将相机坐标系下的坐标转换为右相机坐标系下的坐标:
```python
# 将相机坐标系下的坐标转换为右相机坐标系下的坐标
points2D_left, _ = cv2.projectPoints(points3D_cam, np.zeros(3), np.zeros(3), K_left, dist_left)
points2D_left = np.squeeze(points2D_left)
points2D_right, _ = cv2.projectPoints(points3D_cam, R, t, K_right, dist_right)
points2D_right = np.squeeze(points2D_right)
points3D_right = cv2.triangulatePoints(K_left.dot(R), t, K_right, np.zeros(4), points2D_left.T, points2D_right.T)
points3D_right /= points3D_right[3]
points3D_right = points3D_right[:3].T
```
最终,`points3D_right`就是在右相机下的坐标。
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