SCA 2023: Eurographics/SIGGRAPH Symposium on Computer Animation
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Browsing SCA 2023: Eurographics/SIGGRAPH Symposium on Computer Animation by Author "Kry, Paul G."
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Item Adaptive Rigidification of Discrete Shells(ACM Association for Computing Machinery, 2023) Mercier-Aubin, Alexandre; Kry, Paul G.; Wang, Huamin; Ye, Yuting; Victor ZordanWe present a method to improve the computation time of thin shell simulations by using adaptive rigidification to reduce the number of degrees of freedom. Our method uses a discretization independent metric for bending rates, and we derive a membrane strain rate to curvature rate equivalence that permits the use of a common threshold. To improve accuracy, we enhance the elastification oracle by considering both membrane and bending deformation to determine when to rigidify or elastify. Furthermore, we explore different approaches that are compatible with the previous work on adaptive rigidifcation and enhance the accuracy of the elastification on new contacts without increasing the computational overhead. Additionally, we propose a scaling approach that reduces the conditioning issues that arise from mixing rigid and elastic bodies in the same model.Item Too Stiff, Too Strong, Too Smart: Evaluating Fundamental Problems with Motion Control Policies(ACM Association for Computing Machinery, 2023) Xie, Kaixiang; Xu, Pei; Andrews, Sheldon; Zordan, Victor B.; Kry, Paul G.; Wang, Huamin; Ye, Yuting; Victor ZordanDeep reinforcement learning (DRL) methods have demonstrated impressive results for skilled motion synthesis of physically based characters, and while these methods perform well in terms of tracking reference motions or achieving complex tasks, several concerns arise when evaluating the naturalness of the motion. In this paper, we conduct a preliminary study of specific quantitative metrics for measuring the naturalness of motion produced by DRL control policies beyond their visual appearance. Namely, we propose to study the stiffness of the control policy, in anticipation that it will influence how the character behaves in the presence of external perturbation. Second, we establish two baselines for strength that allow evaluating the use of joint torques in comparison to human performance. Third, we propose the study of variability to reveal the unnatural precision of control policies and how they compare to real human motion. In sum, we aim to establish repeatable measures to assess the naturalness of control policies produced by DRL methods, and we present a set of comparisons from state-of-the-art systems. Finally, we propose simple modifications to improve realism on these axes.