Manual / Auto exposure correlates with depth performance?

erik jakaskerl

Hi we have additional question about this issue.

1. we tested depth performance with OAK-D and OAK-D Pro. But based on our test results, OAK-D Pro is worse than OAK-D now.

   <the result of OAK-D depth test>

   actual measurement | measurement | standard deviation (last 30 data) unit: m

   0.4 0.3996 0.0004

   0.8 | 0.7984 | 0.0010

   1.2 | 1.1994 | 0.0028

   1.6 | 1.5965 | 0.0056

   2.0 | 1.9874 | 0.0085

   2.5 | 2.4747 | 0.0109

   3.0 | 2.9966 | 0.0144

   <the result of OAK-D-Pro depth test>

   actual measurement measurement standard deviation (last 30 data) unit: m

   0.4 | 0.4145 | 0.0004

   0.8 | 0.8587 | 0.0016

   1.2 | 1.3298 | 0.0026

   1.6 | 1.8337 | 0.0059

   2.0 | 2.3776 | 0.0084

   2.5 | 3.1465 | 0.0196

   3.0 | 3.9321 | 0.0334

So we tested OAK-D Pro with depth-preview.py.

<Bright environment>

<Without IR dot projector in a less bright environment>

<with IR dot projector in a less bright environment>

<ir dot projector>

2. I'm using depthai_ros noetic branch of gitgub, and I'm using stereo_inertial_node.launch from depthai_example package. But when i checked its hz(fps), it is working with 20hz. But we would expect 30 hz. i would like to cross-check it with you once more.

   

3. As a result of observing the depth for about 10 minutes at a specific distance (2m), it saw that the measured value gradually went down from 2.02m to 1.94m. do you have any solution for it?

4. i added all the back data for its investigation on the google drive. if you need anything more, please let us know we will follow up as soon as possible.

https://drive.google.com/drive/folders/1ECZGkdMZ8tsw4o2-hzUi-EzzWmKxVKS7?usp=share_link

Best regards,

Ryan.

@"erik"#p7250

Sorry i posted my question during the editing. I uploaded all. And is it possible for me to give me the distance value? 2m or 3 m?? like this. And also why it is worse with close range?? we are wondering about it.

Thank you so much about your great help.

Best regards,

Ryan.

erik Hi

Here is the test method we did. if you need anything more, please feel free to let me know we will come back to you as soon as possible. we also try to prepare the left/right steams and calibration as well.

Test method (attach the measured depth data (0.4m ~ 3.0m))

We are using depthai_ros noetic branch of gitgub, and stereo_inertial_node.launch from depthai_example package.

Depth accuracy was tested by placing an appropriately sized box in front of the camera and moving it in the Z-axis direction relative to the camera frame.

We received the /stereo_inertial_publisher/stereo/depth topic of type sensor_msgs/Image and defined it as the depth to measure the average of 64 pixel data coming in front 8x8 (pixels).

The standard deviation in the third column is the standard deviation of the last 30 depth data measured for objects at a fixed distance.

<the result of OAK-D depth test>

actual measurement | measurement | standard deviation (last 30 data) unit: m

0.4 0.3996 0.0004

0.8 | 0.7984 | 0.0010

1.2 | 1.1994 | 0.0028

1.6 | 1.5965 | 0.0056

2.0 | 1.9874 | 0.0085

2.5 | 2.4747 | 0.0109

3.0 | 2.9966 | 0.0144

<the result of OAK-D-Pro depth test>

actual measurement | measurement | standard deviation (last 30 data) unit: m

0.4 | 0.4145 | 0.0004

0.8 | 0.8587 | 0.0016

1.2 | 1.3298 | 0.0026

1.6 | 1.8337 | 0.0059

2.0 | 2.3776 | 0.0084

2.5 | 3.1465 | 0.0196

3.0 | 3.9321 | 0.0334

Best regards,

Ryan.

Hi Erik erik

Thank you for your support.

here is the information for you. please let me know if you need anything more.

1. calibration data

   
   

   <calibration intrinsics>

   left mono camera intrinsics in pixels:

   [806.3150024414062, 0.0, 629.9376831054688]

   [0.0, 806.3150024414062, 393.29144287109375]

   [0.0, 0.0, 1.0]

   right mono camera intrinsics in pixels:

   [803.0247802734375, 0.0, 636.837646484375]

   [0.0, 803.0247802734375, 413.8108215332031]

   [0.0, 0.0, 1.0]

2. measurement scripts

3. recordings of the left/right streams

Thanks,

Best regards,

Ryan.