A strategy for selecting optimal vergence pose and calibration patterns for stereo-vision calibration

Abstract

The usage of stereo-vision in Automobile, Automation, machine-vision, Infotainment etc. is growing these days enormously day by day. To design a stereo-vision camera, we need to know optimal vergence pose between two cameras as well as number of stereo-pairs required for calibration so that stereo-vision can yield dense disparity map, precise 3D reconstruction, higher stereo-calibration accuracy as well as lower calibration time. This paper addresses these problems of stereo-vision prior to calibration by selecting optimal vergence pose between two cameras and optimal number of stereo-calibration pattern pairs for calibration. To estimate optimal vergence pose, a set of virtual stereo-calibrations patterns are generated by varying Euler angles and it is observed that stereo-reprojection error decreases as Roll angle reduces and exhibits mirror image property and is less sensitive to the variations in Yaw and Pitch. Also to estimate the optimal number of stereo-calibration pattern pairs, an epipolar constraint error was used in eliminating redundant pairs thereby reducing stereo-calibration time and lower stereo-reprojection error. � 2015 IEEE.