Functionality-Driven Musculature Retargeting

Functionality-Driven Musculature Retargeting

Hoseok Ryu    Minseok Kim    Seungwhan Lee    Moon Seok Park    Kyoungmin Lee    Jehee Lee

Seoul National University   


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 examinations.


Hoseok Ryu, Minseok Kim, Seungwhan Lee, Moon Seok park, Kyoungmin Lee, and Jehee Lee.
Functionality-Driven Musculature Retargeting.
Computer Graphics Forum, Volume 40 (2021), Number 1: 341-356.
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Demo video


Source Code

Code is available in Github