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Muscles of the Anterior Neck01:26

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The anterior neck muscles are the group of muscles covering the front part of the neck. These muscles are classified into three subgroups. The first one is the superficial muscles, the most visible muscles in the front of the neck. It includes the platysma and sternocleidomastoid. The second group is the suprahyoid muscles, located above the hyoid bone. This group comprises the digastric, mylohyoid, geniohyoid, and stylohyoid. Lastly, the infrahyoid muscles are found below the hyoid bone and...
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Data-Driven 3D Neck Modeling and Animation.

Yilong Liu, Chengwei Zheng, Feng Xu

    IEEE Transactions on Visualization and Computer Graphics
    |January 17, 2020
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    Summary
    This summary is machine-generated.

    This study introduces a novel 3D neck animation model that separates local larynx motion from global head movements. This data-driven approach enhances facial animation realism and enables speech-driven neck animation.

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    Area of Science:

    • Computer Graphics
    • Animation
    • Biomechanical Modeling

    Background:

    • Realistic 3D neck animation is crucial for character expressiveness in digital media.
    • Existing methods often struggle to capture the complex interplay between larynx motion, head pose, and facial expressions.

    Purpose of the Study:

    • To develop a data-driven approach for realistic 3D neck modeling and animation.
    • To create a neck animation model that decomposes motion into local and global components.
    • To enable speech-driven control of neck animation.

    Main Methods:

    • A novel neck animation model decomposing animation into local (larynx motion) and global (head pose, expressions, speech) deformations.
    • A skinning model for local deformation and larynx motion.
    • Corrective blendshapes for global neck deformation.
    • A regression method to drive larynx motion and neck deformation from speech.
    • Learning the model and regressor from a dataset of 3D neck animation sequences.

    Main Results:

    • The proposed neck model significantly improves the realism of facial animation.
    • The method allows for the creation of plausible neck animations driven by speech and facial expressions.
    • Demonstrated advantages in 3D neck tracking and animation applications.

    Conclusions:

    • The developed data-driven neck model offers a significant advancement in realistic 3D character animation.
    • The approach provides a flexible and effective way to generate nuanced neck movements.
    • The method has practical implications for improving character expressiveness in various digital applications.