Homography Based Egomotion Estimation with a Common Direction

O. Saurer, P. Vasseur, R. Boutteau, C. Demonceaux, M. Pollefeys, Friedrich Fraundorfer

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we explore the different minimal solutions for egomotion estimation of a camera based on homography knowing the gravity vector between calibrated images. These solutions depend on the prior knowledge about the reference plane used by the homography. We then demonstrate that the number of matched points can vary from two to three and that a direct closed-form solution or a Grobner basis based solution can be derived according to this plane. Many experimental results on synthetic and real sequences in indoor and outdoor environments show the efficiency and the robustness of our approach compared to standard methods.
Original languageEnglish
Pages (from-to)327-341
Number of pages15
JournalIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume39
Issue number2
DOIs
Publication statusPublished - 1 Feb 2017

Keywords

  • Cameras
  • Closed-form solutions
  • Estimation
  • Gravity
  • Robustness
  • Three-dimensional displays
  • Transmission line matrix methods
  • Computer vision
  • egomotion estimation
  • homography estimation
  • structure-from-motion

Fingerprint

Dive into the research topics of 'Homography Based Egomotion Estimation with a Common Direction'. Together they form a unique fingerprint.

Cite this