A fast and robust solution to the five-point relative pose problem using Gauss-newton optimization on a manifold

Michel Sarkis*, Klaus Diepold, Knut Hüper

*Corresponding author for this work

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

    16 Citations (Scopus)

    Abstract

    Extracting the motion parameters of a moving camera is an important issue in computer vision. This is due to the need of numerous emerging applications like telepresence and robot navigation. The key issue is to determine a robust estimate of the (3×3) essential matrix with its five degrees of freedom. In this work, a robust technique to compute the essential matrix is suggested under the assumption that the images are calibrated. The algorithm is a combination of the five-point relative pose problem using an optimization technique on a manifold, with the random sample consensus. The results show that the proposed, method delivers faster and more accurate results than the standard techniques.

    Original languageEnglish
    Title of host publication2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
    PagesI681-I684
    DOIs
    Publication statusPublished - 2007
    Event2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, HI, United States
    Duration: 15 Apr 200720 Apr 2007

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume1
    ISSN (Print)1520-6149

    Conference

    Conference2007 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
    Country/TerritoryUnited States
    CityHonolulu, HI
    Period15/04/0720/04/07

    Fingerprint

    Dive into the research topics of 'A fast and robust solution to the five-point relative pose problem using Gauss-newton optimization on a manifold'. Together they form a unique fingerprint.

    Cite this