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Covariance Propagation and Next Best View Planning for 3D Reconstruction

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Author

Editor

  • Andrew Fitzgibbon
  • Svetlana Lazebnik
  • Pietro Perona
  • Yoichi Sato
  • Cordelia Schmid

Summary, in English

This paper examines the potential benefits of applying next best view planning to sequential 3D reconstruction from unordered image sequences. A standard sequential structure-and-motion pipeline is extended with active selection of the order in which cameras are resectioned. To this end, approximate covariance propagation is implemented throughout the system, providing running estimates of the uncertainties of the reconstruction, while also enhancing robustness and accuracy. Experiments show that the use of expensive global bundle adjustment can be reduced throughout the process, while the additional cost of propagation is essentially linear in the problem size.

Publishing year

2012

Language

English

Pages

545-556

Publication/Series

Computer Vision – ECCV 2012 12th European Conference on Computer Vision, Florence, Italy, October 7-13, 2012, Proceedings, Part II (Lecture Notes in Computer Science 7573)

Volume

7573

Document type

Conference paper

Publisher

Springer

Topic

  • Computer Vision and Robotics (Autonomous Systems)
  • Mathematics

Conference name

12th European Conference on Computer Vision (ECCV 2012)

Conference date

2012-10-07 - 2012-10-13

Conference place

Florence, Italy

Status

Published

Research group

  • Mathematical Imaging Group

ISBN/ISSN/Other

  • ISSN: 0302-9743
  • ISSN: 1611-3349
  • ISBN: 978-3-642-33709-3
  • ISBN: 978-3-642-33708-6 (Print)