6
votes
Accepted
How do I estimate the pose of a camera looking at a flat horizontal surface?
Your problem is called pose estimation. The OpenCV function is called solvePnP(). Be aware that the intrinsic camera matrix must be known in advance.
If you don't ...
- 531
5
votes
How do I estimate the pose of a camera looking at a flat horizontal surface?
All of this is written assuming that you have already calibrated the camera for its intrinsic matrix. If you have not done this, then you need to do so beforehand, or you need to look to the answer ...
- 11.7k
4
votes
Camera Calibration - why do you have to move the calibration board?
This is due to the optimization problem being rather high-dimensional (around 11 parameters). With only a single observation of the calibration board, there would be multiple possible combinations of ...
- 146
3
votes
Accepted
Math for projecting 3d world point to VR image coordinates
Your images look like being shot with an angular fisheye projection . Also, to account for epipolar geometry of stereo images, you should include the fundamental matrix into the transform engine of ...
- 1,589
3
votes
Estimating Plane Pose Without Knowledge of Intrinsic Camera Parameters
I think there is a mistake in this part:
\begin{equation}
\vec{n} = K \vec{R_1} \times K \vec{R_2} = det(K)K^{-T}(\vec{R_1}\times\vec{R_2})\end{equation}
In particular, if $\alpha \neq 1$
\begin{...
- 31
2
votes
Accepted
Pinhole camera model from houdini parameters
This is a long topic to fully explain. I will try to write shortly, so please excuse the brevity.
Standard computer vision projection (ignoring distortion like Houdini) follows:
$$
\mathbf{x} = \...
- 5,445
2
votes
Accepted
Camera calibration vs. registration
There is no matrix that maps a pixel in camera 1 to the corresponding pixel in camera 2. This is because the location of the corresponding pixel depends on the 3-D location of the corresponding point ...
- 5,071
2
votes
How do I estimate the pose of a camera looking at a flat horizontal surface?
I deleted my previous answer because I was glued in some convoluted calculations and the question was answered with a nice on-the-shelf software answer. However since then I continued to look into ...
- 442
2
votes
Accepted
Intuition about tag pose estimation accuracy
The size of the tag is an important parameter. But it is a secondary parameter. The key parameter that we are looking at here (and one that is not easy to estimate) is Signal to Noise Ratio (SNR). So, ...
- 10.5k
1
vote
Accepted
Understanding difference in rotation and translation
Homography has an interpretation as a change of perspective or movement of the "camera". I think your example casually refers to the apparent "rotation" of the camera in the ...
- 171
1
vote
Find camera pose by knowing triangle coordinates
No. No. You can't.
Not completely at least. With only three points, the math has two solutions. Your triangle could be tilted in one of two positions. Like picking a square root.
From a single ...
- 7,492
1
vote
Accepted
Camera Pose Estimation from Vanishing Points
You can use the vanishing points to calibrate the camera.
I recommend reading Chapter 8.6 of Multiple View Geometry in Computer Vision [ http://www.cambridge.org/9780521540513 ]
Even better, if you ...
- 26
1
vote
Camera Calibration - why do you have to move the calibration board?
Digital cameras sample the incoming optical EM or photonic field with a fixed grid of CCD or CMOS transistors. Since the sampling grid (rectangular or perhaps hexagonal) is not angularly symmetric, ...
- 35.1k
1
vote
Accepted
Which pattern (circle pattern or checkerboard pattern) should be used for automotive camera calibration (fisheye/wide webcam)?
The answer here suggests that checkerboard patterns may yield more accurate (subpixel) calibration results and be more robust.
You may have edited your question because the title asks which pattern ...
- 26
1
vote
Accepted
How are the scaling parameters included (extracted from) an essential matrix?
The Essential matrix is defined only up to scale, so you cannot extract scale from it. In other words, if you multiply $t$ and all the 3D world points in your scene by a constant factor, the essential ...
- 5,071
1
vote
Obtain motion between image features by means of the homography matrix
First, calibrate your intrinsics: The focal lengths and the principal point. Homography is not really a rigid transformation and rather a mapping of a plane onto another one. What you really need is a ...
- 5,445
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