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A Joint Sensing Framework for Real-time Mobile Camera Localization

Zeng, Jiuming LU and Hua, Yanling LU (2025) MAMM15 20251
Department of Design Sciences
Abstract
In this paper, a joint perception framework combining fixed and mobile cameras is proposed, which can achieve accurate real-time positioning of the mobile camera in a unified coordinate system. The system integrates VGGT for high-precision pose estimation and combines it with MASt3r-SLAM for robust real-time tracking. Alignment between different coordinate systems is achieved through rotation matrix transformation and Procrustes analysis. User evaluation confirms the effectiveness of the system in indoor navigation scenarios and is expected to help visually impaired users. Although the framework is sensitive to motion blur, it shows strong flexibility, high accuracy, and effective use of multi-source image data. Future work will focus on... (More)
In this paper, a joint perception framework combining fixed and mobile cameras is proposed, which can achieve accurate real-time positioning of the mobile camera in a unified coordinate system. The system integrates VGGT for high-precision pose estimation and combines it with MASt3r-SLAM for robust real-time tracking. Alignment between different coordinate systems is achieved through rotation matrix transformation and Procrustes analysis. User evaluation confirms the effectiveness of the system in indoor navigation scenarios and is expected to help visually impaired users. Although the framework is sensitive to motion blur, it shows strong flexibility, high accuracy, and effective use of multi-source image data. Future work will focus on enhancing robustness to blurred inputs, extending the framework to support 4D scene reconstruction, and developing advanced auxiliary navigation functions to pave the way for practical applications. (Less)
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author
Zeng, Jiuming LU and Hua, Yanling LU
supervisor
organization
course
MAMM15 20251
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Real-time Camera Localization, Camera Pose Estimation, Joint Sensing, SLAM, 3D Foundation Models
language
English
id
9193418
date added to LUP
2025-06-05 12:08:47
date last changed
2025-06-05 12:08:47
@misc{9193418,
  abstract     = {{In this paper, a joint perception framework combining fixed and mobile cameras is proposed, which can achieve accurate real-time positioning of the mobile camera in a unified coordinate system. The system integrates VGGT for high-precision pose estimation and combines it with MASt3r-SLAM for robust real-time tracking. Alignment between different coordinate systems is achieved through rotation matrix transformation and Procrustes analysis. User evaluation confirms the effectiveness of the system in indoor navigation scenarios and is expected to help visually impaired users. Although the framework is sensitive to motion blur, it shows strong flexibility, high accuracy, and effective use of multi-source image data. Future work will focus on enhancing robustness to blurred inputs, extending the framework to support 4D scene reconstruction, and developing advanced auxiliary navigation functions to pave the way for practical applications.}},
  author       = {{Zeng, Jiuming and Hua, Yanling}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{A Joint Sensing Framework for Real-time Mobile Camera Localization}},
  year         = {{2025}},
}