Self Image Rectification for Uncalibrated Stereo Video with Varying Camera Motions and Zooming Effects

In this paper, we propose a novel self image rectification algorithm for uncalibrated stereo video sequences. Different from conventional stereo systems, this algorithm performs adaptive calibration that allows unequal motions and zooming effects in both cameras. For the first stereo frame, we estimate a reduced set of camera parameters through a nonlinear optimization process to minimize the geometric errors of the corresponding points in pre-rectified image coordinates. For the subsequent frames, these parameters are updated via minimizing the objective function that jointly considers the geometric errors and the smoothness constraints over temporal variations. The experimental results of applying this algorithm to two real sequences are shown to demonstrate its superior performance in reliable rectification distortions and robustness against outliers.