Sparse Rig Parameter Optimization for Character Animation

How to read this

Category

Method: an optimization for motion retargeting into rig space

Contributions

• Optimizes sparse rig parameter values that reproduce a target pose or motion with minimal source error
• Uses an intermediate object to transfer motion from varied sources onto production rigs
• Adds sparsity regularization to activate only necessary controls plus keyframe extraction for editable output

Context

Relates to learning inverse rig mappings for character animation (e.g. Holden et al.'s Learning an Inverse Rig Mapping), but emphasizes sparsity and editability so the retargeted result stays artist-friendly.Builds on: Learning an Inverse Rig Mapping for Character Animation

Correctness

Assumes that a sparse activation of controls can adequately reproduce the source motion while preserving editability; the value depends on the chosen sparsity regularizer and on the rigs tested, so a reader should weigh reconstruction error against the cleanliness of the resulting curves.

Clarity

Moderately technical; a first pass conveys the goal (sparse, editable retargeting), a second pass is needed for the optimization formulation.

How to read it

First pass for the problem framing (sparsity plus editability); do a second pass on the objective and the sparsity term if you care about clean retargeted keyframes.