DISCLAIMER: Apologies for this very large question, as it could take a lot of your time.
I have a stereo setup consisting of two webcams these cameras possess auto-focus technology. The stereo setup is in canonical configuration where the cameras are separated by 10 cm distance.
I am using the stereo_calib.cpp program for stereo calibration, provided by the OpenCV sample programs.
Initially, I have captured the chessboard images by my stereo rig as the way it is shown in the sample cpp stereo images, and then tried to calibrate the setup, but the stereo rectification was either completely blank or the undistorted left and right images are tilted about 40 degrees.
As this was the case, then I have captured a set of 17 stereo pair chessboard images by keeping the Z distance constant, without any rotation, at this point the stereo images were correctly rectified in the process of stereo calibration. This Working Set contains the images of chessboard taken by the stereo setup along with the program and the image of how well the rectification has been achieved.
Later, when I was trying to calibrate the stereo setup again (as the cameras in the stereo setup was disturbed), with another new set of images of the chessboard taken by my stereo rig, the program is unable to rectify the stereo images. I am providing the Non Working Set where you can check the images taken by the stereo setup along with the images of the rectification.
As a picture is worth a thousand words.
You gotta see the output images of the provided program, which let you know much more than what I could say in my own words.
I am trying to find some new ways of stereo face recognition techniques.
Any help in this regard is highly appreciated.
And adding to this, I also need some existing techniques by which I could kick start my experimentation on new ways of face recognition using the stereo information.