Relative pose estimation for a multi-camera system with known vertical direction

Gim Hee Lee*, Marc Pollefeys, Friedrich Fraundorfer

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperpeer-review


In this paper, we present our minimal 4-point and linear 8-point algorithms to estimate the relative pose of a multi-camera system with known vertical directions, i.e. known absolute roll and pitch angles. We solve the minimal 4-point algorithm with the hidden variable resultant method and show that it leads to an 8-degree univariate polynomial that gives up to 8 real solutions. We identify a degenerated case from the linear 8-point algorithm when it is solved with the standard Singular Value Decomposition (SVD) method and adopt a simple alternative solution which is easy to implement. We show that our proposed algorithms can be efficiently used within RANSAC for robust estimation. We evaluate the accuracy of our proposed algorithms by comparisons with various existing algorithms for the multi-camera system on simulations and show the feasibility of our proposed algorithms with results from multiple real-world datasets.

Original languageEnglish
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
PublisherIEEE Computer Society
Number of pages8
ISBN (Electronic)9781479951178, 9781479951178
Publication statusPublished - 24 Sept 2014
EventCVPRW 2014: IEEE Conference on Computer Vision and Pattern Recognition Workshops - Columbus, United States
Duration: 23 Jun 201428 Jun 2014


ConferenceCVPRW 2014
Abbreviated titleCVPRW 2014
Country/TerritoryUnited States


  • Generalized Camera
  • Known Vertical Direction
  • Minimal Problem
  • Multi-Camera System
  • Relative Pose Estimation

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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