“Muscle-Based Facial Retargeting with Anatomical Constraints” by Cong and Fedkiw

  • ©Matthew D Cong and Ronald Fedkiw

  • ©Matthew D Cong and Ronald Fedkiw

  • ©Matthew D Cong and Ronald Fedkiw



Entry Number: 05


    Muscle-Based Facial Retargeting with Anatomical Constraints



    We present a physically based facial retargeting algorithm that is suitable for use in high-end production. Given an actor’s facial performance, we first run a targeted muscle simulation on the actor in order to determine the actor blendshape muscles that best match the performance. The deformation of the actor blendshape muscles are then transferred onto the creature to obtain the corresponding creature blendshape muscles. Finally, the resulting creature blendshape muscles are used to drive a creature muscle simulation which yields the retargeted performance. In order to ensure the anatomically correct placement of the muscles, cranium, and jaw, we introduce novel anatomically motivated constraints during the transfer process. Compared to previous approaches, these constraints not only improve the expressiveness of the retargeted creature performance to the actor performance but also eliminate spurious visual artifacts.


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    Matthew Cong, Michael Bao, Jane L. E, Kiran S. Bhat, and Ronald Fedkiw. 2015. Fully Automatic Generation of Anatomical Face Simulation Models. In Proc. of the 14th ACM SIGGRAPH / Eurographics Symposium on Computer Animation. 175–183.

    Matthew Cong, Kiran S. Bhat, and Ronald Fedkiw. 2016. Art-Directed Muscle Simulation for High-End Facial Animation. In Proc. of the ACM SIGGRAPH/Eurographics  Symposium on Computer Animation. 119–127.

    Matthew Cong, Lana Lan, and Ronald Fedkiw. 2017. Muscle Simulation for Facial Animation in Kong: Skull Island. In ACM SIGGRAPH 2017 Talks (SIGGRAPH ’17). ACM, New York, NY, USA, Article 21, 2 pages.

    Lana Lan, Matthew Cong, and Ronald Fedkiw. 2017. Lessons from the Evolution of an Anatomical Facial Muscle Model. In Proceedings of the ACM SIGGRAPH Digital Production Symposium (DigiPro ’17). ACM, New York, NY, USA, Article 11, 3 pages.

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