depth estimation using stereo cameras

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Hi, I want to implement depth esimation with stereo cameras.
after rectification, the images should follow this rule: objects that are closer to the cameras should have large disparity and vice versa.
but in my results there is a far object with relative big disparity. I have noticed that in the following image, that I took from matlab example, there is a similar case (the car at the end of the parking lot) .
My question is why does this happen? and would it damage the depth estimation?
I'll just add that the I used the calibration app one time, and feature detector and estimateFundamentalMatrix function a second time. both gave similar results.

Accepted Answer

Dima Lisin
Dima Lisin on 21 Sep 2015
Edited: Dima Lisin on 21 Sep 2015
Hi Idan,
When you do uncalibrated rectification, the rectified views do not always end up parallel, but may be verged a little. That means the disparity may actually be negative for objects that are far away. I think this is what happened to the car at the end of the parking lot. In a case like this, if you compute the disparity map, you should subtract the minimum disparity value from the map. This will shift the range, to make the minimum disparity 0.
  2 Comments
Dima Lisin
Dima Lisin on 21 Sep 2015
This can happen if camera 1 is to the right of camera 2, as you look in the same direction as the cameras. In that case, the sign of disparity values is reversed. Generally it is a good idea to make sure that camera 1 is on the left.

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