Possible approaches for processing of spherical images using SfM

Abstract

Spherical cameras are being used more frequently in surveying because of their low cost and possibility to process spherical images with conventional SfM methods. Fish-eye lenses are now frequently found on modern 360° cameras, allowing for the capture of the entire scene and subsequent model reconstitution by a non-photogrammetrist specialist. Gyrospherics are a feature of cameras that ensure image stabilization to reduce blur when the camera is moving. This feature allows it to capture moving scenes in time-lapse mode. However, two main factors - hardware parameters and software algorithms - affect the quality of the images that are captured. The 360° camera design allows for a variety of data processing methods by SfM. These images were created using multiple image sensors and lenses from each 360° camera. These images can be processed individually or by applying rules to define relationships between images. Also, images from cameras can be stitched and processed with a spherical camera model. In this paper is proposed processing methods of data from 360° cameras and estimated accuracy of each method.