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Related Experiment Video

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Photorealistic Learned Landscapes for Augmented Reality
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Image-Based Models for Specularity Propagation in Diminished Reality.

Souheil Hadj Said, Mohamed Tamaazousti, Adrien Bartoli

    IEEE Transactions on Visualization and Computer Graphics
    |May 26, 2017
    PubMed
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    This study introduces a new method for Diminished Reality (DR) to seamlessly remove objects from videos. The approach effectively handles illumination changes by propagating specularities, significantly improving rendering quality.

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    Area of Science:

    • Computer Vision
    • Computer Graphics
    • Virtual Reality

    Background:

    • Diminished Reality (DR) aims to seamlessly remove target objects from live video streams.
    • Replacing removed object areas with new textures requires seamless blending and propagation across frames.
    • Updating the target region for illumination changes, especially with viewpoint shifts, remains a significant challenge in current DR techniques.

    Purpose of the Study:

    • To address the limitations of state-of-the-art DR in handling illumination changes.
    • To develop novel models for specularity propagation to improve rendering quality in DR.
    • To enhance the seamless removal of objects in live video streams under varying lighting conditions.

    Main Methods:

    • Utilizing local illumination models where illumination variations primarily affect the specular component of an image.
    • Developing two new models for specularity propagation based on identified structural properties of specularities.
    • Employing a Thin-Plate Spline-based estimation method in the first model for illumination smoothness.
    • Incorporating specularity shape properties on planar surfaces in the second model.

    Main Results:

    • Demonstrated that existing DR methods struggle with illumination changes, even in simple scenarios.
    • Proposed models significantly improve rendering quality compared to current state-of-the-art DR techniques.
    • Experimental results on both synthetic and real-world data validate the effectiveness of the new strategy.

    Conclusions:

    • The proposed specularity propagation models offer a substantial improvement for Diminished Reality.
    • Handling illumination changes through specularity propagation is a viable and effective approach for DR.
    • The new methods enhance the realism and seamlessness of object removal in dynamic video environments.