Homography estimation on the Special Linear group based on direct point correspondence

Tarek Hamel*, Robert Mahony, Jochen Trumpf, Pascal Morin, Minh Duc Hua

*Corresponding author for this work

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

    26 Citations (Scopus)

    Abstract

    This paper considers the question of obtaining a high quality estimate of a time-varying sequence of image homographies using point correspondences from an image sequence without requiring explicit computation of the individual homographies between any two given images. The approach uses the representation of a homography as an element of the Special Linear group and defines a nonlinear observer directly on this structure. We assume, either that the group velocity of the homography sequence is known, or more realistically, that the homographies are generated by rigid-body motion of a camera viewing a planar surface, and that the angular velocity of the camera is known.

    Original languageEnglish
    Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages7902-7908
    Number of pages7
    ISBN (Print)9781612848006
    DOIs
    Publication statusPublished - 2011
    Event2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, FL, United States
    Duration: 12 Dec 201115 Dec 2011

    Publication series

    NameProceedings of the IEEE Conference on Decision and Control
    ISSN (Print)0743-1546
    ISSN (Electronic)2576-2370

    Conference

    Conference2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
    Country/TerritoryUnited States
    CityOrlando, FL
    Period12/12/1115/12/11

    Fingerprint

    Dive into the research topics of 'Homography estimation on the Special Linear group based on direct point correspondence'. Together they form a unique fingerprint.

    Cite this