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Video-Based 3D Reconstruction: A Review of Photogrammetry and Visual SLAM Approaches.

Ali Javadi Moghadam1, Abbas Kiani1, Reza Naeimaei2

  • 1Department of Geomatics, Faculty of Civil Engineering, Babol Noshirvani University of Technology, Babol 4714871167, Iran.

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|March 27, 2026
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Summary

This study explores video-based 3D reconstruction methods, focusing on keyframe extraction for enhanced accuracy and efficiency in computer vision and photogrammetry applications like robotics and mapping.

Keywords:
3D reconstructionV-SLAMkeyframe extractionreal-time 3D reconstructionvideogrammetry

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Area of Science:

  • Computer Vision and Photogrammetry
  • Robotics and Augmented Reality
  • 3D Mapping and Modeling

Background:

  • Three-dimensional (3D) reconstruction from images is crucial for robotics, AR, and mapping.
  • Video data, particularly monocular video, is increasingly utilized for 3D reconstruction.
  • Existing research includes Structure from Motion (SfM), Multi-View Stereo (MVS), and Visual Simultaneous Localization and Mapping (V-SLAM).

Purpose of the Study:

  • To investigate and categorize various video-based 3D reconstruction methods.
  • To identify trends and advancements in the field through statistical analysis of publications.
  • To provide recommendations for improving keyframe extraction in real-time 3D reconstruction.

Main Methods:

  • Analysis of SCOPUS records for publication trends (approx. 6863 publications).
  • Detailed review of ~80 selected studies on video-based 3D reconstruction techniques.
  • Investigation of photogrammetry-based methods versus V-SLAM for real-time applications.
  • Examination of IMU data and image quality metrics for frame selection.

Main Results:

  • Video-based 3D reconstruction is dominated by photogrammetry (high accuracy, high computation) and V-SLAM (real-time, high speed).
  • Keyframe extraction is identified as a critical step for efficient and accurate reconstruction.
  • IMU data and image quality indicators aid in selecting optimal frames for reconstruction.

Conclusions:

  • The study categorizes video-based 3D reconstruction methods, highlighting keyframe extraction's importance.
  • Recommendations are provided to enhance accuracy and efficiency in real-time reconstruction.
  • Future research should address dynamic scenes, computational costs, and learning-based integration.