Depth estimation from stereo cameras through a curved transparent medium

Seongwook Yoon, Taehyeon Choi, Sanghoon Sull

    Research output: Contribution to journalArticlepeer-review

    9 Citations (Scopus)

    Abstract

    In this paper, we propose a novel method for estimating depth values by stereo cameras through a curved transparent medium that causes refraction. Our method takes both the surface shape of the medium and the refraction into account. We model that the rays from the stereo cameras are refracted by a curved transparent medium whose inner surface is represented by a parametric model, assuming that the medium has constant thickness. The parameters of the model are estimated using a constrained optimization simply by attaching several markers on the inner surface. The depth value is then estimated by the triangulation considering the refraction based on the model. The experimental results show that our method yields consistently high error reduction rates with respect to the baseline method without considering the refraction caused by the medium. In addition, our method provides satisfactory estimates for various shapes of the medium.

    Original languageEnglish
    Pages (from-to)101-107
    Number of pages7
    JournalPattern Recognition Letters
    Volume129
    DOIs
    Publication statusPublished - 2020 Jan

    Bibliographical note

    Publisher Copyright:
    © 2019

    Keywords

    • Camera calibration
    • Depth from stereo
    • Parametric surface model
    • Refraction

    ASJC Scopus subject areas

    • Software
    • Signal Processing
    • Computer Vision and Pattern Recognition
    • Artificial Intelligence

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