Co-viewpoint Multi-camera Combined Calibration for Optical Circle-imaging System

In this paper, we propose a multi-camera combined calibration method for co-viewpoint circle-imaging system to obtain panoramic images. In recent years, high-resolution images are applied in wide fields of artificial intelligence to satisfy various scenes, such as tele-observation, 3D environment reconstruction and road detection. But most common methods are based on complicated matching algorithm processing. The result has high precision but also costs much time to deal with images captured by cameras. However, the optical circle-imaging system in this paper only applies simple cropping and splicing to image matrix instead of feature points matching among images captured by different cameras or at different angles. And in order to carry out the calibration and adjust positions of cameras in this system, we design an improved template consisting of three identical chessboards with settled relationship between every two boards. Once the system is constructed, it can give the panorama in a short time with high resolution and accuracy.