Abstract

Abstract. Image-based virtual reality (VR) is a virtual space generated with panoramic images projected onto a primitive model. In imagebased VR, realistic VR scenes can be generated with lower rendering cost, and network data can be described as relationships among VR scenes. The camera network data are generated manually or by an automated procedure using camera position and rotation data. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Thus, we focused on image-based VR generation using a panoramic camera in indoor environments. We propose a methodology to automate network data generation using panoramic images for an image-based VR space. We verified and evaluated our methodology through five experiments in indoor environments, including a corridor, elevator hall, room, and stairs. We confirmed that our methodology can automatically reconstruct network data using panoramic images for image-based VR in indoor environments without GNSS position data.

Highlights

  • Virtual reality (VR) is a 3D virtual space in which users can experience a real space with 3D computer graphics using a VR theater or wearable devices

  • Model-based VR is a virtual space with a 3D model generated using CAD software products, and the 3D model is generated from point cloud data acquired via laser scanning and structure from motion (SfM) processing (Snavely, 2010)

  • When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data

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Summary

Introduction

Virtual reality (VR) is a 3D virtual space in which users can experience a real space with 3D computer graphics using a VR theater or wearable devices. The network data are generated manually or by an automated procedure using camera position and rotation data This manual work requires much time to link with each VR scene. When panoramic images are acquired in indoor environments, network data should be generated without Global Navigation Satellite Systems (GNSS) positioning data. Corridors are difficult environments for image-based VR generation with indoor positioning data, because the multipass problems in radio propagation make the positioning environment in corridors unstable. Based on these technical issues, a new methodology is required to generate network data to connect the panorama images acquired with submeter steps in indoor environments. We evaluated the processing performance of our proposed algorithm through five experiments in indoor environments

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