A linear approach to motion estimation using generalized camera models

Hongdong Li*, Richard Hartley, Jae Hak Kim

*Corresponding author for this work

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

    102 Citations (Scopus)

    Abstract

    A well-known theoretical result for motion estimation using the generalized camera model is that 17 corresponding image rays can be used to solve linearly for the motion of a generalized camera. However, this paper shows that for many common configurations of the generalized camera models (e.g., multi-camera rig, catadioptric camera etc.), such a simple 17-point algorithm does not exist, due to some previously overlooked ambiguities. We further discover that, despite the above ambiguities, we are still able to solve the motion estimation problem effectively by a new algorithm proposed in this paper. Our algorithm is essentially linear, easy to implement, and the computational efficiency is very high. Experiments on both real and simulated data show that the new algorithm achieves reasonably high accuracy as well.

    Original languageEnglish
    Title of host publication26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
    DOIs
    Publication statusPublished - 2008
    Event26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR - Anchorage, AK, United States
    Duration: 23 Jun 200828 Jun 2008

    Publication series

    Name26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

    Conference

    Conference26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR
    Country/TerritoryUnited States
    CityAnchorage, AK
    Period23/06/0828/06/08

    Fingerprint

    Dive into the research topics of 'A linear approach to motion estimation using generalized camera models'. Together they form a unique fingerprint.

    Cite this