cv2.calibrateHandEye在提供3x1旋转向量或3x3旋转矩阵时输出不同的结果
cv2.calibrateHandEye在提供3x1旋转向量或3x3旋转矩阵时输出不同的结果
提问于 2020-12-12 02:13:14
我目前正在尝试使用opencv的手眼校准函数(cv2.calibrateHandEye())来校准Microsoft Azure Kinect。然而，当我插入3x1旋转向量作为输入，而不是3x3旋转矩阵时，我得到了与所有方法完全不同的结果。下面，我将分享我在这两种情况下得到的输出。
我想知道为什么会出现这种差异，因为我使用cv2.Rodrigues在向量和矩阵之间进行转换。
3x1 Rotation Vector case:
(19, 3) (19, 3) (19, 3) (19, 3)
--------------------------------------
Method 0
Rotation:
[[1. 0. 0.]
[0. 1. 0.]
[0. 0. 1.]]
Translation:
[[0.]
[0.]
[0.]]
--------------------------------------
--------------------------------------
Method 1
Rotation:
[[nan nan nan]
[nan nan nan]
[nan nan nan]]
Translation:
[[0.]
[0.]
[0.]]
--------------------------------------
--------------------------------------
Method 2
Rotation:
[[-1. 0. 0.]
[ 0. -1. 0.]
[ 0. 0. 1.]]
Translation:
[[0.]
[0.]
[0.]]
--------------------------------------
--------------------------------------
Method 3
Rotation:
[[-0.03388477 0.81429681 0.57945882]
[ 0.37003643 -0.52836555 0.76413538]
Translation:
[[0.]
[0.]
[0.]]
--------------------------------------
--------------------------------------
Method 4
Rotation:
[[nan nan nan]
[nan nan nan]
[nan nan nan]]
Translation:
[[nan]
[nan]
[nan]]
--------------------------------------
3x3 Rotation Matrix case:
(19, 3, 3) (19, 3) (19, 3, 3) (19, 3)
--------------------------------------
Method 0
Rotation:
[[ 0.19681749 0.15272093 -0.96847261]
[-0.9802481 0.01110192 -0.19745987]
[-0.01940435 0.988207 0.15188945]]
Translation:
[[426.01991564]
[ 6.31112392]
[212.62483639]]
--------------------------------------
--------------------------------------
Method 1
Rotation:
[[ 4.38898532e-04 7.05825236e-02 9.97505847e-01]
[-9.99993453e-01 -3.55184483e-03 6.91318082e-04]
[-3.59178096e-03 9.97499620e-01 -7.05805026e-02]]
Translation:
[[ 113.83854629]
[ -64.48053741]
[-155.89394605]]
--------------------------------------
--------------------------------------
Method 2
Rotation:
[[-1.63313542e-04 1.12303599e-01 -9.93673928e-01]
[-9.99994011e-01 -3.45353893e-03 -2.25961739e-04]
[-3.45706791e-03 9.93667940e-01 1.12303491e-01]]
Translation:
[[429.63163945]
[-72.98653944]
[228.31050502]]
--------------------------------------
--------------------------------------
Method 3
Rotation:
[[ 0.27525174 0.87240146 0.403921 ]
[ 0.20267468 0.35804992 -0.91144019]
[-0.93976564 0.33274006 -0.07825982]]
Translation:
[[-126.85624931]
[ 205.9095892 ]
[ 90.09963159]]
--------------------------------------
--------------------------------------
Method 4
Rotation:
[[-0.20970054 0.33923475 -0.91703079]
[-0.94475058 -0.31195916 0.1006371 ]
[-0.25193655 0.88746902 0.38591023]]
Translation:
[[ 716.47999662]
[-112.67040497]
[ 604.15236449]]
--------------------------------------回答 1
Stack Overflow用户
发布于 2021-12-02 13:21:18
对你来说可能太晚了，但对其他人来说可能很有趣:我偶然发现了同样的bug，在我的例子中，我有一个用于R_gripper2base的Mat向量。我使用push_back将实际的旋转放在列表的末尾。当我使用向量作为输入时，一切都很好，但使用罗德里格斯矩阵时，push_back不仅将实际矩阵放在末尾，还更改了列表中其他所有条目的值。所以最后我得到了一个矩阵的向量，它们都是一样的。这就是为什么calibrateHandEye的结果很糟糕。
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/65256538
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