Structure from Motion for omnidirectional images using efficient factorization method based on virtual camera rotation

Abstract— The estimation of a 3D shape of a scene as well as the position and the orientation of the sensor has been extensively researched, especially for Virtual Reality (VR) and Robotics systems. To achieve this estimation, a system that consists of a laser range sensor, Global Positioning System (GPS), and Gyro sensor has been proposed, actually constructed, and used. However, it is usually difficult to produce a precise and detailed estimation of the 3D shape because of the limited ability of each sensor. The Structure from Motion (SFM) method is widely known for estimation purposes, and the method can estimate those parameters accurately through pixel resolution. However, the SFM method is frequently unstable because of dependency on initial parameters and also because of noise. In this paper, we propose an SFM method for omnidirectional image sequences using both factorization and a bundle adjustment method to achieve high accuracy and robustness.