Full-body musculoskeletal model for muscle-driven simulation of human gait

A Rajagopal, CL Dembia, MS DeMers… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
Objective: Musculoskeletal models provide a noninvasive means to study human movement
and predict the effects of interventions on gait. Our goal was to create an open-source 3-D …

Numerical instability of Hill-type muscle models

SH Yeo, J Verheul, W Herzog… - Journal of the Royal …, 2023 - royalsocietypublishing.org
Hill-type muscle models are highly preferred as phenomenological models for
musculoskeletal simulation studies despite their introduction almost a century ago. The use …

Rignet: Neural rigging for articulated characters

Z Xu, Y Zhou, E Kalogerakis, C Landreth… - arxiv preprint arxiv …, 2020 - arxiv.org
We present RigNet, an end-to-end automated method for producing animation rigs from
input character models. Given an input 3D model representing an articulated character …

Neuroskinning: Automatic skin binding for production characters with deep graph networks

L Liu, Y Zheng, D Tang, Y Yuan, C Fan… - ACM Transactions on …, 2019 - dl.acm.org
We present a deep-learning-based method to automatically compute skin weights for
skeleton-based deformation of production characters. Given a character mesh and its …

Synthesis of biologically realistic human motion using joint torque actuation

Y Jiang, T Van Wouwe, F De Groote… - ACM Transactions On …, 2019 - dl.acm.org
Using joint actuators to drive the skeletal movements is a common practice in character
animation, but the resultant torque patterns are often unnatural or infeasible for real humans …

Phace: Physics-based face modeling and animation

AE Ichim, P Kadleček, L Kavan, M Pauly - ACM Transactions on …, 2017 - dl.acm.org
We present a novel physics-based approach to facial animation. Contrary to commonly used
generative methods, our solution computes facial expressions by minimizing a set of non …

Reinforcement learning control of a biomechanical model of the upper extremity

F Fischer, M Bachinski, M Klar, A Fleig, J Müller - Scientific Reports, 2021 - nature.com
Among the infinite number of possible movements that can be produced, humans are
commonly assumed to choose those that optimize criteria such as minimizing movement …

Inferring forces and learning human utilities from videos

Y Zhu, C Jiang, Y Zhao, D Terzopoulos… - Proceedings of the …, 2016 - cv-foundation.org
We propose a notion of affordance that takes into account physical quantities generated
when the human body interacts with real-world objects, and introduce a learning framework …

Softcon: Simulation and control of soft-bodied animals with biomimetic actuators

S Min, J Won, S Lee, J Park, J Lee - ACM Transactions on Graphics …, 2019 - dl.acm.org
We present a novel and general framework for the design and control of underwater soft-
bodied animals. The whole body of an animal consisting of soft tissues is modeled by …

Breathing life into biomechanical user models

A Ikkala, F Fischer, M Klar, M Bachinski… - Proceedings of the 35th …, 2022 - dl.acm.org
Forward biomechanical simulation in HCI holds great promise as a tool for evaluation,
design, and engineering of user interfaces. Although reinforcement learning (RL) has been …