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.
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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