Stereo image calibration using angle constraints

Abstract

Stereo images have to be calibrated before stereo vision can recover the 3D information of the imaged scene. Position constraints via point correspondences are traditionally used to solve the calibration problem. We describe a method that uses correspondences of projections of orthogonal trihedral vertices for calibration. The method has a closed-form solution, as opposed to many other calibration methods which are iterative. It also requires only two vertex correspondences at minimum to recover all the transformation parameters which are recoverable from a stereo image pair. Extensive experimental results including those on real images are presented, and they show that our method is more robust than those using position constraints alone.