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Review Article | Open Access | Just Accepted

3D Indoor Scene Geometry Estimation from a Single Omnidirectional Image: A Comprehensive Survey

Ming Meng1, Yonggui Zhu1, Yufei Zhao1, Zhaoxin Li2, Zhe Zhu3( )

1 School of Data Science and Media Intelligence, Communication University of China, Beijing, 100024, China

2 Agricultural Information Institute, Chinese Academy of Agricultural Sciences, No. 12, Zhongguancun South Street, Beijing, 100081, Beijing, China

3 Samsung Research America, USA

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Abstract

This paper surveys the technology used in threedimensional indoor scene geometry estimation from a single 360◦ omnidirectional image, which is pivotal in extracting 3D structural information from indoor environments. The technology transforms omnidirectional data into a 3D model, depicting spatial structure, object positions, and scene layout. Its significance spans various domains, including virtual reality (VR), augmented reality (AR), mixed reality (MR), game development, urban planning, and robot navigation.We begin by revisiting foundational concepts of omnidirectional imaging and detailing the problems, applications, and challenges in this field. Our review categorizes the fundamental tasks of structure recovery, depth estimation, and layout recovery. We also review pertinent datasets and evaluation metrics, providing the latest research as a reference. Finally, we summarize the field and discuss potential future trends to inform and guide further research.

Keywords

3D scene geometryomnidirectional imagesstructure recoverydepth estimationlayout recovery
Computational Visual Media
Cite this article:
Meng M, Zhu Y, Zhao Y, et al. 3D Indoor Scene Geometry Estimation from a Single Omnidirectional Image: A Comprehensive Survey. Computational Visual Media, 2024, https://doi.org/10.26599/CVM.2025.9450438

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Received: 31 January 2024
Accepted: 24 April 2024
Available online: 27 June 2024

© The Author(s) 2024.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

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Other papers from this open access journal are available free of charge from http://www.springer.com/journal/41095. To submit a manuscript, please go to https://www.editorialmanager.com/cvmj.
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