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Geodesic Binding for Degenerate Character Geometry Using Sparse Voxelization.

Olivier Dionne, Martin de Lasa

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    We present an automatic method for generating character skinning weights. This approach handles complex 3D models and allows interactive weight adjustments for artists.

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    Area of Science:

    • Computer Graphics
    • Geometric Modeling
    • Animation

    Background:

    • Character skinning methods like linear blend skinning and dual quaternion skinning are crucial in 3D animation.
    • Specifying accurate influence weights for these methods can be complex and time-consuming.
    • Production meshes often present challenges such as non-manifold geometry and non-watertight surfaces.

    Purpose of the Study:

    • To develop a fully automatic method for specifying influence weights for closed-form skinning techniques.
    • To create a system that efficiently handles complex and imperfect production 3D meshes.
    • To enable interactive weight modification for artists without additional pre-processing.

    Main Methods:

    • The proposed method voxelizes the input character rest pose mesh and skeleton hierarchy.
    • Binding weights are calculated using geodesic distances between skeleton bone voxels and non-exterior mesh voxels.
    • The system decouples weight assignment from distance computation for interactive adjustments.

    Main Results:

    • The method generates smooth skinning weights at interactive rates.
    • It successfully handles production meshes with non-manifold geometry, non-watertight surfaces, intersecting triangles, and multiple components.
    • Weight modification can be performed interactively at pose time without re-computation.

    Conclusions:

    • This automatic method simplifies the process of assigning influence weights for character skinning.
    • It offers an efficient and flexible solution for artists working with complex 3D assets.
    • The interactive nature of the weight adjustment empowers artists to refine character deformations more effectively.