Single-frame real-time three-dimensional imaging method based on deep learning
By constructing a lightweight phase retrieval network and a multi-vision structured light projection system, combined with GPU acceleration technology, real-time single-frame 3D imaging was achieved. This solved the problems of high computational resource consumption and difficulty in imaging dynamic scenes in existing methods, and achieved efficient and real-time 3D imaging results.
Patent Information
- Application Number
- PCT/CN2025/131477
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2024-11-19
- Filing Date
- 2025-10-31
- Publication Date
- 2026-05-28
AI Technical Summary
Existing single-frame deep learning methods struggle to achieve real-time, high-precision 3D imaging in complex and dynamic scenes. Furthermore, traditional structured light 3D imaging requires multiple shots and consumes significant computational resources, making it unsuitable for real-time applications.
A deep learning-based real-time single-frame 3D imaging method was designed. By constructing a lightweight phase retrieval network model and building a multi-view structured light stripe projection system, a real-time single-frame 3D imaging method was achieved by utilizing multi-view geometric constraints and stereo phase matching algorithms, combined with GPU acceleration technology.
It achieves real-time, high-precision 3D imaging in complex and dynamic scenes, overcomes the computational resource limitations of traditional methods, provides efficient 3D reconstruction capabilities, and is suitable for real-time application scenarios.
Smart Images
Figure CN2025131477_28052026_PF_FP_ABST