Stereo Depth Accuracy¶
Stereo depth accuracy (Z-Accuracy) depends on number of factors that are documented at Improving stereo accuracy. In a nutshell, the most important factors are:
Camera calibration: Accuracy results below were obtained with the default factory calibration.
FOV of the camera: Wider FOV results in less accurate depth.
Resolution of stereo pair: Higher resolution results in more accurate depth.
Baseline distance: Wider baseline distance results in more accurate depth, but also higher MinZ (minimal depth distance the camera can detect).
800P, 75mm baseline distance OAKs¶
0.7m - 4m: below 1% absolute depth error
4m - 7m: below 2% absolute depth error
7m - 12m: below 3% absolute depth error
480P, 75mm baseline distance OAKs¶
40cm - 3m: below 2% absolute depth error
3m - 6m: below 4% absolute depth error
6m - 8m: below 6% absolute depth error
We are using random noise pattern to measure depth accuracy, so the lighting/texture (documentation here) is near-ideal. This means that random dot projector (on Pro versions) won’t make a difference. The noise pattern board is parpendicular to the camera, and the camera is looking at the center of the board. We are using highest stereo resolution possible, always have subpixel enabled with 5 disparity bits (to provide the best accuracy), and aren’t using any On-Device Stereo Postprocessing Filters).
Here is the process for each step of the measurement, which is similar to how other companies measure their depth accuracy:
Capture the image, find ROI of the noise pattern board (via markers)
Remove invalid pixels and outliers (top/bottom 5% of values)
Calculate median of remaining depth values
Repeat 10 times, average the median values to remove noise
Raw data of the depth accuracy evaluation can be found on Google Sheets here.