Issue |
J. Eur. Opt. Society-Rapid Publ.
Volume 20, Number 1, 2024
|
|
---|---|---|
Article Number | 18 | |
Number of page(s) | 18 | |
DOI | https://doi.org/10.1051/jeos/2024018 | |
Published online | 03 May 2024 |
Review Article
Overview of image-based 3D reconstruction technology
1
Shijiazhuang Campus, Army Engineering University of PLA, Shijiazhuang 050003, PR China
2
32398 units of PLA, Beijing 100192, PR China
* Corresponding author: liulimin0807@aeu.edu.cn
Received:
9
December
2023
Accepted:
8
April
2024
Three-dimensional (3D) reconstruction technology is the key technology to establish and express the objective world by using computer, and it is widely used in real 3D, automatic driving, aerospace, navigation and industrial robot applications. According to different principles, it is mainly divided into methods based on traditional multi-view geometry and methods based on deep learning. This paper introduces the above methods from the perspective of three-dimensional space representation. The feature extraction and stereo matching theory of traditional 3D reconstruction methods are the theoretical basis of 3D reconstruction methods based on deep learning, so the paper focuses on them. With the development of traditional 3D reconstruction methods and the development of deep learning related theories, the explicit deep learning 3D reconstruction method represented by MVSNet and the implicit 3D reconstruction method represented by NeRF have been gradually developed. At the same time, the dataset and evaluation indicators for 3D reconstruction were introduced. Finally, a summary of image based 3D reconstruction was provided.
Key words: 3D reconstruction / Multi-view geometry / Deep learning
© The Author(s), published by EDP Sciences, 2024
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