← ArchivePaper2021
Functionality-Driven Musculature Retargeting
Hoseok Ryu, Minseok Kim, Seunghwan Lee, Moon Seok Park, Kyoungmin Lee, Jehee Lee
Transfers musculature from a reference anatomical model to bodies of different proportions while preserving functionality and producing simulation-ready results.
Abstract
We present a novel retargeting algorithm that transfers the musculature of a reference anatomical model to new bodies with different sizes, body proportions, muscle capability, and joint range of motion while preserving the functionality of the original musculature as closely as possible. The geometric configuration and physiological parameters of musculotendon units are estimated and optimized to adapt to new bodies. The range of motion around joints is estimated from a motion capture dataset and edited further for individual models. The retargeted model is simulation‐ready, so we can physically simulate muscle‐actuated motor skills with the model. Our system is capable of generating a wide variety of anatomical bodies that can be simulated to walk, run, jump and dance while maintaining balance under gravity. We will also demonstrate the construction of individualized musculoskeletal models from bi‐planar X‐ray images and medical examination.
How to read this
- Category
- Method: musculature retargeting for simulation-ready anatomical models
- Contributions
- A retargeting algorithm that transfers a reference musculature to bodies of different size, proportion, muscle capability and joint range of motion while preserving functionality
- Estimates and optimizes geometric configuration and physiological parameters of musculotendon units, with range of motion estimated from motion capture
- Produces simulation-ready models, including individualized musculoskeletal models built from bi-planar X-ray images and medical examination
- Context
- Extends muscle-actuated human simulation and control, building directly on Lee et al.'s scalable muscle-actuated simulation.Builds on: Scalable Muscle-Actuated Human Simulation and Control
- Correctness
- Validated by physically simulating retargeted models walking, running, jumping and dancing under gravity; functionality is preserved as closely as possible rather than exactly, and quality depends on the reference model and the motion capture used to estimate range of motion.
- Clarity
- Moderately technical (CGF); a first pass conveys the goal and pipeline, a second pass is needed for the parameter optimization.
- How to read it
- Read for the retargeting pipeline and what simulation-ready means here; second pass on the musculotendon parameter estimation if you work with muscle simulation.
Builds on
Related work
Keywords
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