AURORA: Automated Unleash of 3D Room Outlines for VR Applications

TL;DR

AURORA is an automated method that uses RGB-D images to generate accurate and realistic 3D room outlines for VR applications, streamlining the creation of virtual environments from real-world data.

Contribution

It introduces a novel integration of image processing, segmentation, and 3D reconstruction techniques to automate and improve indoor scene generation for VR.

Findings

Effective generation of detailed virtual scenes from real-world environments.

Demonstrated high accuracy and realism on multiple datasets.

Streamlined process benefits VR design workflows.

Abstract

Creating realistic VR experiences is challenging due to the labor-intensive process of accurately replicating real-world details into virtual scenes, highlighting the need for automated methods that maintain spatial accuracy and provide design flexibility. In this paper, we propose AURORA, a novel method that leverages RGB-D images to automatically generate both purely virtual reality (VR) scenes and VR scenes combined with real-world elements. This approach can benefit designers by streamlining the process of converting real-world details into virtual scenes. AURORA integrates advanced techniques in image processing, segmentation, and 3D reconstruction to efficiently create realistic and detailed interior designs from real-world environments. The design of this integration ensures optimal performance and precision, addressing key challenges in automated indoor design generation by uniquely combining and leveraging the strengths of foundation models. We demonstrate the effectiveness of our approach through experiments, both on self-captured data and public datasets, showcasing its potential to enhance virtual reality (VR) applications by providing interior designs that conform to real-world positioning.