Absolute and Relative Pose Estimation in Refractive Multi View

Xiao Hu, Francois Lauze, Kim Steenstrup Pedersen, Jean Melou

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


    This paper investigates absolute and relative pose estimation under refraction, which are essential problems for refractive structure from motion. We first present an absolute pose estimation algorithm by leveraging an efficient iterative refinement. Then, we derive a novel refractive epipolar constraint for relative pose estimation. The epipolar constraint is established based on the virtual camera transformation, making it in a succinct form and can be efficiently optimized. Evaluations of the proposed algorithms on synthetic data show superior accuracy and computational efficiency to state-of-the-art methods. For further validation, we demonstrate the performance on real data and show the application in 3D reconstruction of objects under refraction.
    Original languageEnglish
    Title of host publicationProceedings - 2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW 2021)
    Publication date2021
    ISBN (Electronic)978-1-6654-0191-3
    Publication statusPublished - 2021
    Event2021 International Conference on Computer Vision - Virtual event
    Duration: 11 Oct 202117 Oct 2021


    Conference2021 International Conference on Computer Vision
    LocationVirtual event
    Internet address


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