Stereo Calibration and Rectification for Omnidirectional Multi-Camera Systems

Abstract

Stereo vision has been studied for decades as a fundamental problem in the field of computer vision. In recent years, computer vision and image processing with a large field of view, especially using omnidirectional vision and panoramic images, has been receiving increasing attention. An important problem for stereo vision is calibration. Although various kinds of calibration methods for omnidirectional cameras are proposed, most of them are limited to calibrate catadioptric cameras or fish-eye cameras and cannot be applied directly to multi-camera systems. In this work, we propose an easy calibration method with closed-form initialization and iterative optimization for omnidirectional multi-camera systems. The method only requires image pairs of the 2D target plane in a few different views. A method based on the spherical camera model is also proposed for rectifying omnidirectional stereo pairs. Using real data captured by Ladybug3, we carry out some experiments, including stereo calibration, rectification and 3D reconstruction. Statistical analyses and comparisons of the experimental results are also presented. As the experimental results show, the calibration results are precise and the effect of rectification is promising.