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# How can I improve ZED Camera precision?

2018-08-10 17:40:11

I'm using Stereolabs ZED camera for my computer vision project. I did a small research about several sensors on the market and ultimately we decided to go with the ZED Camera.

However I'm finding that the precision of the camera isn't that great. And the Point Cloud takes too much storage space. Anyone found the same problems? And if so, how did you managed them?

Thank you!

I don't know what you mean by "precision" and how do you measure it. The sensing

accuracy will probably go back to the camera calibration precision and the stereo matching algorithm used. If they ship the device "calibrated" then no one knows what happened after the camera was calibrated in factory and before you got it (mechanical shock, temperature swings) - so you better re-calibrate it yourself (with OpenCV, Matlab etc.).

If you are interested in the depth accuracy from stereo vision itself then see the following equation:

dz = (z^2 * de) / (f * b)

where dz is the depth error in meters

• I don't know what you mean by "precision" and how do you measure it. The sensing

accuracy will probably go back to the camera calibration precision and the stereo matching algorithm used. If they ship the device "calibrated" then no one knows what happened after the camera was calibrated in factory and before you got it (mechanical shock, temperature swings) - so you better re-calibrate it yourself (with OpenCV, Matlab etc.).

If you are interested in the depth accuracy from stereo vision itself then see the following equation:

dz = (z^2 * de) / (f * b)

where dz is the depth error in meters, z is the depth in meters, de is the disparity error in pixels, f is the focal length of the camera in pixels and b is the camera baseline in meters. The main message of the equation above is that the depth error grows with the square of depth (distance from camera) itself.

You get better depth accuracy the bigger f and b are. Given the ZED camera has both of these relatively small - baseline

2018-08-10 18:17:30
• For improved precision try calibrating the camera with the Stereo Camera Calibrator app in MATLAB.

As far as the memory taken up by the point cloud, that really depends on how many points you have. You can always try reducing the resolution of the cameras, downsampling the point cloud itself, and/or using a lower precision data type to store the coordinates.

2018-08-10 18:55:17
• This paper shows an approximation of the RMS error of the ZED camera as a function of distance.Depth Data Error Modeling of the ZED 3D Vision Sensor from Stereolabs

2018-08-10 19:50:21