Solving for muscle blending using data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10432183" target="_blank" >RIV/00216208:11320/20:10432183 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Yih_1mqa4l" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Yih_1mqa4l</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.cag.2020.09.005" target="_blank" >10.1016/j.cag.2020.09.005</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Solving for muscle blending using data

Popis výsledku v původním jazyce

Modeling of the human face is a challenging yet important problem in computer graphics. Building accurate muscle models for physics-based simulation of the face is a problem that either requires a lot of manual effort or drastic over-parameterization of the muscles to achieve desirable results. In this work, we reduce the number of parameters required to build personalized muscle models by taking into account the blending of the fine muscles and passive tissue when we solve for the muscle activations. We begin by adapting an anatomical template model to a neutral scan of a subject. Then, we solve an inverse physics problem using several scans simultaneously to solve for both the muscle activations and the geometry matrix representing blending of the muscles. Finally, we demonstrate that this geometry matrix can be used on new, previously unseen scans to solve for only the muscle activations. This greatly reduces the number of parameters that must be solved for compared to previous works while requiring no additional manual effort in constructing the muscles. (C) 2020 Elsevier Ltd. All rights reserved.

Název v anglickém jazyce

Solving for muscle blending using data

Popis výsledku anglicky

Modeling of the human face is a challenging yet important problem in computer graphics. Building accurate muscle models for physics-based simulation of the face is a problem that either requires a lot of manual effort or drastic over-parameterization of the muscles to achieve desirable results. In this work, we reduce the number of parameters required to build personalized muscle models by taking into account the blending of the fine muscles and passive tissue when we solve for the muscle activations. We begin by adapting an anatomical template model to a neutral scan of a subject. Then, we solve an inverse physics problem using several scans simultaneously to solve for both the muscle activations and the geometry matrix representing blending of the muscles. Finally, we demonstrate that this geometry matrix can be used on new, previously unseen scans to solve for only the muscle activations. This greatly reduces the number of parameters that must be solved for compared to previous works while requiring no additional manual effort in constructing the muscles. (C) 2020 Elsevier Ltd. All rights reserved.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2020

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Computers and Graphics

ISSN

0097-8493

e-ISSN

—

Svazek periodika

2020

Číslo periodika v rámci svazku

92

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

9

Strana od-do

67-75

Kód UT WoS článku

000605063100008

EID výsledku v databázi Scopus

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