Computing Skinning Weights via Convex Duality

Abstract We study the problem of optimising for skinning weights through the lens of convex duality. In particular, we show that the popular bounded biharmonic weight (BBW) model for skinning is dual to a non‐negative least‐squares problem, which is amenable to efficient solution via iterative algorithms; the final weights are then recoverable via a closed‐form expression. Our formulation maintains convexity and is provably equivalent to the original problem. We also provide theoretical discussion giving intuition for the dual problem in the smooth case. Our final algorithm, which can be implemented in a few lines of code, achieves efficient convergence times relative to generic quadratic programming tools applied to the primal problem, without nonconvex formulations, relaxations or specialised optimisation techniques.

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Publication Details

Journal
Computer Graphics Forum
Published
2025-09-25
DOI
https://doi.org/10.1111/cgf.70159
Primary Topic
Digital Image Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

Computing Skinning Weights via Convex Duality

Justin Solomon, O. Stein
Computer Graphics Forum
Digital Image Processing Techniques
article

Computing Skinning Weights via Convex Duality

Justin Solomon, O. Stein
article en

Abstract

Abstract We study the problem of optimising for skinning weights through the lens of convex duality. In particular, we show that the popular bounded biharmonic weight (BBW) model for skinning is dual to a non‐negative least‐squares problem, which is amenable to efficient solution via iterative algorithms; the final weights are then recoverable via a closed‐form expression. Our formulation maintains convexity and is provably equivalent to the original problem. We also provide theoretical discussion giving intuition for the dual problem in the smooth case. Our final algorithm, which can be implemented in a few lines of code, achieves efficient convergence times relative to generic quadratic programming tools applied to the primal problem, without nonconvex formulations, relaxations or specialised optimisation techniques.

Computer Graphics Forum
University of Southern California (US), Massachusetts Institute of Technology (US)
Openalex Percentile: Top 74%
Digital Image Processing Techniques
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