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Improved Feature Matching for Mobile Devices with IMU.

Andrea Masiero1, Antonio Vettore2

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Summary

This study enhances photogrammetry for smartphones by integrating inertial navigation system (INS) data. This improves feature matching for 3D reconstruction, making it more robust and efficient.

Keywords:
3D reconstructionfeature matchinginertial navigation systemphotogrammetrysmartphones

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Area of Science:

  • Computer Vision
  • Geomatics Engineering
  • Robotics

Background:

  • Photogrammetry is increasingly used for environmental surveys, driven by accessible high-resolution cameras and automated 3D reconstruction techniques.
  • Automatic feature matching is crucial for accurate 3D scene geometry estimation in photogrammetry.
  • Utilizing smart mobile devices for photogrammetry presents unique challenges in feature matching.

Purpose of the Study:

  • To improve the robustness and computational efficiency of feature matching for 3D photogrammetric reconstruction using smart mobile devices.
  • To leverage inertial navigation system (INS) data to enhance feature matching accuracy.
  • To develop a more efficient and reliable method for estimating the essential matrix (E) and camera pose.

Main Methods:

  • A revised, computationally less complex version of the Affine Scale-Invariant Feature Transform (ASIFT) was employed.
  • Information from the inertial navigation system (INS) was integrated to aid feature matching.
  • A novel two-step procedure was introduced for estimating the essential matrix (E) and camera pose.

Main Results:

  • The revised ASIFT method demonstrated increased correct feature matches compared to the original SIFT.
  • Integration of INS data enhanced the robustness of the feature matching process.
  • The proposed two-step procedure improved both the robustness and computational efficiency of essential matrix estimation.

Conclusions:

  • Combining INS data with a revised ASIFT algorithm offers a more robust and efficient approach to photogrammetric feature matching on mobile devices.
  • The developed method enhances the accuracy of 3D reconstruction from smartphone imagery.
  • This research contributes to the advancement of mobile-based photogrammetry for various applications.