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Weber_Power_Bundle_Adjustment_for_Large-Scale_3D_Reconstruction_CVPR_2023_paper.pdf
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🔗 Source: openaccess.thecvf.com
📊 Size: 4.39 MB
👤 Author: Simon Weber; Nikolaus Demmel; Tin Chon Chan; Daniel Cremers
⬇️ Downloads: 110

Summary

Power Bundle Adjustment (PoBA) is introduced as a novel solver for large-scale bundle adjustment problems, leveraging power series expansion of the inverse Schur complement. The approach theoretically justifies the use of power series and proves convergence, demonstrating significant acceleration and improved accuracy compared to state-of-the-art iterative methods. PoBA is shown to be faster and more memory-efficient, with evaluations on the BAL dataset and incorporation into a distributed BA framework yielding improved speed and accuracy. The solver is released as open source.

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Description

Power Bundle Adjustment (PoBA) is introduced as a novel solver for large-scale bundle adjustment problems, leveraging power series expansion of the inverse...

Technical Information

  • File Format: PDF
  • File Size: 4.39 MB
  • Pages: 9
  • Language: EN
  • Author: Simon Weber; Nikolaus Demmel; Tin Chon Chan; Daniel Cremers
  • Total Downloads: 110
  • Last Updated: 16 hours ago

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