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Hello everyone,

I have computed a disparity map using OpenCV on Python, but my goal is to get the real depth from this disparity map.

Steps accomplished :

1. Take 40 calibration pictures with 2 side by side cameras
2. Calibrate each camera individually using the cv2.calibrateCamera() function
3. Stereo calibration with the cv2.stereoCalibrate() function
4. Compute rotation matrix with the cv2.stereoRectify() function
5. Undistort both of the cameras with the cv2.initUndistortRectifyMap() function
6. Use Stereo SGBM algorithm to create a disparity map
7. Ajust Stereo SGBM parameters to get the best possible result for the disparity map
8. Use cv2.reprojectImageTo3D() function to get real 3D coordinates (depth map)

All my results until point 7) seem to be correct (see images below).

However, the result given by cv2.reprojectImageTo3D() is totally incorrect, and I am unable to understand where is the problem. The calibration has been done with units in [cm], so for an object placed at 50 cm, the result should be near 50, but the function returns -0.6. Any idea what could be the problem ?

My results are the following, for a bottle placed at 50cm of the 2 cameras :

Images after undistortion :

Disparity map

Depth (-3.64 represents a white pixel, manually added in the disparity map for visualization purposes, as you can see on the above image) :

Any help would be very welcome !

Hello everyone,

I have computed a disparity map using OpenCV on Python, but my goal is to get the real depth from this disparity map.

Steps accomplished :

1. Take 40 calibration pictures with 2 side by side cameras
2. Calibrate each camera individually using the cv2.calibrateCamera() function
3. Stereo calibration with the cv2.stereoCalibrate() function
4. Compute rotation matrix with the cv2.stereoRectify() function
5. Undistort both of the cameras with the cv2.initUndistortRectifyMap() function
6. Use Stereo SGBM algorithm to create a disparity map
7. Ajust Stereo SGBM parameters to get the best possible result for the disparity map
8. Use cv2.reprojectImageTo3D() function to get real 3D coordinates (depth map)

All my results until point 7) seem to be correct (see images below).

However, the result given by cv2.reprojectImageTo3D() is totally incorrect, and I am unable to understand where is the problem. The calibration has been done with units in [cm], so for an object placed at 50 cm, the result should be near 50, but the function returns -0.6. Any idea what could be the problem ?

My results are the following, for a bottle placed at 50cm of the 2 cameras :

Images after undistortion :

Disparity map

Depth Map (-3.64 represents a white pixel, manually added in the disparity map for visualization purposes, as you can see on the above image) image. Every pixels near the value should be around 50, but it gives -0.6) :

Any help would be very welcome !