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Updated: Feb 13, 2026

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Robust approach to reconstructing transparent objects using a time-of-flight depth camera.

Kyungmin Kim, Hyunjung Shim

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    |March 10, 2018
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new method for 3-D reconstruction of translucent objects using depth cameras. The approach improves accuracy and reliability by incorporating prior models and a depth error model.

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    Area of Science:

    • Computer Vision
    • 3-D Reconstruction
    • Optics

    Background:

    • Reconstructing translucent objects with depth cameras is challenging due to light scattering and environmental interactions.
    • Existing methods for translucent object depth error modeling are often incomplete and sensitive to noise.

    Purpose of the Study:

    • To develop a robust 3-D reconstruction framework for translucent objects using a single time-of-flight depth camera.
    • To overcome limitations of existing methods by introducing novel priors and an improved depth error model.

    Main Methods:

    • Utilized a single time-of-flight depth camera and simple user marks for data acquisition.
    • Introduced a ground plane and a piece-wise linear surface model as priors.
    • Integrated these priors with a depth error model based on the time-of-flight principle.

    Main Results:

    • The proposed method significantly enhances the accuracy of 3-D reconstruction for translucent objects.
    • Demonstrated substantial improvements in the reliability of the reconstruction process.
    • Evaluated performance using extensive real-world data.

    Conclusions:

    • The developed framework offers a robust solution for 3-D reconstruction of challenging translucent objects.
    • The integration of specific priors and an advanced depth error model leads to superior results.
    • This approach advances the capabilities of depth sensing technology for complex object geometries.