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Robust 3D face landmark localization based on local coordinate coding.

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    This study introduces a new method for accurately locating 3D facial landmarks, crucial for 3D face animation. The approach uses local coordinate coding (LCC) and achieves robust and flexible results comparable to existing techniques.

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    Area of Science:

    • Computer Vision
    • Computer Graphics
    • 3D Imaging

    Background:

    • 3D facial animation and synthesis require labeled landmarks for parameterization.
    • Automatic 3D face landmark localization is challenging due to variations in pose, expression, and resolution.

    Purpose of the Study:

    • To present a novel approach for automatic 3D face landmark localization.
    • To address the challenges posed by pose, expression, and resolution variations in 3D face data.

    Main Methods:

    • A two-stage approach based on local coordinate coding (LCC).
    • Stage 1: Nose detection (invariant feature) followed by 3D affine transformation using iterative closest points to align faces.
    • Stage 2: Resampling for correspondence building and LCC-based algorithm for landmark localization.

    Main Results:

    • The proposed method demonstrates robustness, flexibility, and accuracy.
    • Achieves performance comparable to state-of-the-art methods in 3D face landmark localization.

    Conclusions:

    • The novel LCC-based approach effectively overcomes challenges in automatic 3D face landmark localization.
    • The method offers a reliable solution for parameterizing 3D faces in animation and synthesis applications.