Parallel line detection and camera attitude estimation for 360 degree images

Abstract

360-degree cameras are beginning to be widely used for recording and presenting a wide range of scenes such as street view, drive recorders, property introductions, and drone photography. However, most of them use fisheye lenses with large distortion, which often makes it difficult to apply general image processing algorithms. Therefore, although it has the advantage of being able to capture a wide range of scenes, it is not actively used as a three-dimensional shape measurement or various image processing sensors. In this study, I propose a method for detecting straight and parallel lines directly from 360-degree images, and a method for estimating the axial direction and camera orientation of the detected parallel lines. In addition, we simply calibrate the camera internal parameters using horizontal and vertical lines, and report the experimental results comparing the estimation errors of the camera attitude in two ways, calibrated and uncalibrated.