Tool/software:
What is the minumun size (pixel) of the black square (as shown below) in the calibration chart in a FullHD (1920x1080) camera image?
I want to minimize the size of the surround view calibration chart.
Thanks in advance
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Tool/software:
What is the minumun size (pixel) of the black square (as shown below) in the calibration chart in a FullHD (1920x1080) camera image?
I want to minimize the size of the surround view calibration chart.
Thanks in advance
Hello,
Thanks for your question. I'm investigating these details about the surround view application.
Regards,
Sarabesh S.
Thanks for your kindly support in advance. This information would be very helpful for me to minimize the calibrating space.
--Joy
Hi Joy,
No problem, the surround view app support is limited and I haven't gotten a chance to discuss with the team on this topic. I will try to get back to you with more information tomorrow. If not, I will provide an update next week.
Thank you,
Sarabesh S.
Hi Joy,
Still discussing with experts. It seems like this depends on the distance of the field on the chart because that will determine how large the pixels need to be to be able to accurately depict the output image. Will update with more findings as I get them.
Thank you,
Sarabesh S.
I think that the algorithm should not care about the actual size of the chart (in millimeters), but only about the number of pixels (maybe 20pixel, or 40pixel?) the chart occupies in the camera image
For example, the black square of my chart is 112mm and the chart position is shown below:
Here is one of the camera view (1920x1080):
I just wonder what is the minimum pixel of the black square in the camera view is allowed to do surround view calibration and would work.
Thanks in advance.
Joy
Hello Joy,
There is no actual limit on size of the squares. They can be as small as needed as long as you can manually select the points on the square used for calibration. In the older devices this was done through MatLab. However, having larger squares will help the calibration and provide more accurate output images.
Thank you,
Sarabesh S.