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width: 640
distortion_model: "plumb_bob"
D: [0.0, 0.0, 0.0, 0.0, 0.0]
K: [381.36246688113556, 0.0, 320.5, 0.0, 381.36246688113556, 240.5, 0.0, 0.0, 1.0]
R: [1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]
P: [381.36246688113556, 0.0, 320.5, -0.0, 0.0, 381.36246688113556, 240.5, 0.0, 0.0, 0.0, 1.0, 0.0]
binning_x: 0
binning_y: 0
roi: 
x_offset: 0
y_offset: 0
height: 0
width: 0
do_rectify: False
k_int = np.array([[381.36246688113556, 0.0, 320.5],
                  [0.0, 381.36246688113556, 240.5],
                  [0.0, 0.0, 1.0]])

I need the camera matrix and the distortion matrix for AR tag detection.I need to identify the camera matrix which is supposed to be a 3*3 matrix from the above data.But,I am unable to determine it.

corners, ids, _ = aruco.detectMarkers(
                        gray,
                        aruco_dict,
                        parameters=parameters,
                        cameraMatrix=matrix_coefficients,
                        distCoeff=distortion_coefficients)

This is where I need the two matrices.I read on internet about the plumb_bob model and it says there are five parameters for it. [k1,k2,k3,t1,t2].

Someone please help me to understand it.

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1
  • $\begingroup$ Please consider updating your question to include anything that you've already researched along these topics. What library or applications are you trying to use it for? Those will be helpful to someone who wants to help answer your question. $\endgroup$
    – Tully
    Apr 28 at 19:06

1 Answer 1

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I assume you got the camera information from somewhere so I would look at the documentation from that source.

K is the camera matrix and D are the distortion params.

It looks like you got this from ROS. The CameraInfo.msg documentation has all the info you need.

So camera matrix is

$$\begin{bmatrix} 381.36246688113556& 0.0& 320.5 \\ 0.0& 381.36246688113556& 240.5 \\ 0.0 & 0.0& 1.0 \end{bmatrix}$$

And distortion params [k1,k2,k3,t1,t2] is all zeros.

$$ [0.0, 0.0, 0.0, 0.0, 0.0]$$

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