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Rapid 3D Reconstruction for Image Sequence Acquired from UAV Camera.

Yufu Qu1, Jianyu Huang2, Xuan Zhang3

  • 1Department of Measurement Technology & Instrument, School of Instrumentation Science & Optoelectronics Engineering, Beihang University, Beijing 100191, China. qyf@buaa.eud.cn.

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Summary
This summary is machine-generated.

This study introduces a rapid 3D reconstruction method for unmanned aerial vehicle (UAV) images. It significantly speeds up processing for complex scenes with over 100 images, maintaining high precision.

Keywords:
3D reconstructionUAV cameramulti-view stereopoint cloudstructure from motion

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Area of Science:

  • Computer Vision
  • Photogrammetry
  • Robotics

Background:

  • Three-dimensional (3D) reconstruction from image sequences is crucial for various applications.
  • Unmanned Aerial Vehicles (UAVs) provide efficient platforms for image acquisition.
  • Existing methods often face challenges with processing speed, especially for large datasets.

Purpose of the Study:

  • To develop a rapid 3D reconstruction method for UAV camera image sequences.
  • To enhance processing speed without compromising reconstruction accuracy.
  • To address the computational demands of large-scale 3D mapping.

Main Methods:

  • Feature point compression using Principal Component Analysis (PCA).
  • Key image selection based on interrelationship estimation using principal component points.
  • Utilizing a fixed-length image queue and weighted bundle adjustment for pose estimation and 3D coordinate calculation.
  • Depth map calculation and fusion for dense 3D point cloud generation.

Main Results:

  • The proposed method achieves a calculation speed improvement of over four times for complex textures and more than 100 images.
  • Reconstruction precision is maintained with minimal loss.
  • Speed improvement becomes more pronounced as the number of images increases.

Conclusions:

  • The image queue-based rapid 3D reconstruction method offers a significant speed-up for UAV photogrammetry.
  • The approach is particularly effective for large-scale, complex 3D reconstruction tasks.
  • This method provides a practical solution for real-time or near-real-time 3D mapping applications.