A real-time misalignment correction algorithm for stereoscopic 3D cameras

Camera calibration is an important problem for stereo 3-D cameras since the misalignment between the two views can lead to vertical disparities that significantly degrade 3-D viewing quality. Offline calibration during manufacturing is not always an option especially for mass produced cameras due to cost. In addition, even if one-time calibration is performed during manufacturing, its accuracy cannot be maintained indefinitely because environmental factors can lead to changes in camera hardware. In this paper, we propose a real-time stereo calibration solution that runs inside a consumer camera and continuously estimates and corrects for the misalignment between the stereo cameras. Our algorithm works by processing images of natural scenes and does not require the use of special calibration charts. The algorithm first estimates the disparity in horizontal and vertical directions between the corresponding blocks from stereo images. Then, this initial estimate is refined with two dimensional search using smaller sub-blocks. The displacement data and block coordinates are fed to a modified affine transformation model and outliers are discarded to keep the modeling error low. Finally, the estimated affine parameters are split by half and misalignment correction is applied to each view accordingly. The proposed algorithm significantly reduces the misalignment between stereo frames and enables a more comfortable 3-D viewing experience.