Modeling and Estimation of Nonlinear Skin Mechanics for Animated Avatars

Romero, Cristian; Otaduy, Miguel Á.; Casas, Dan; Pérez, Jesús

doi:10.1111/cgf.13913

Cited by 16 publications

(12 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on these definitions, we compute an unposed deformation gradient F = ∇xT = ∇ X (x + u) = I + ∇ X U φ φ. This definition of the deformation gradient resembles the one recently proposed by Romero et al [ROCP20]. However, they discretized kinematics using world positions, not unposed displacements, hence they had to explicitly compute the inverse skinning transformation of positions to compute the deformation gradient.…”

Section: Unposed Deformationmentioning

confidence: 93%

“…Kim et al [KPMP*17] combined the SMPL model with a soft-tissue layer simulated in full space. Very recently, Romero et al [ROCP20] further improved this method by formulating deformations in the unposed reference space to allow external interactions while preserving the accurate static data-driven deformation. In this paper, we combine the previous idea with a local deformation subspace and a custom cubature scheme to allow for real-time simulation of complex skeletal soft models.…”

Section: Soft Skeletal Modelsmentioning

confidence: 99%

“…While SMPL and MANO were originally defined as surfaceonly deformations, Kim et al [KPMP*17], and later Romero et al [ROCP20], developed volumetric extensions that fit the same formulation (1). Since we formulate dynamics in the unposed reference space (Section 4.1), we only need to evaluate the skinning transformation W (•) at the surface, for visualization and contact handling.…”

Section: Parametric Skeletal Modelmentioning

confidence: 99%

See 2 more Smart Citations

Parametric Skeletons with Reduced Soft‐Tissue Deformations

Tapia

Romero

Pérez

et al. 2021

Computer Graphics Forum

Self Cite

View full text Add to dashboard Cite

We present a method to augment parametric skeletal models with subspace soft-tissue deformations. We combine the benefits of data-driven skeletal models, i.e. accurate replication of contact-free static deformations, with the benefits of pure physics-based models, i.e. skin and skeletal reaction to contact and inertial motion with two-way coupling. We succeed to do so in a highly efficient manner, thanks to a careful choice of reduced model for the subspace deformation. With our method, it is easy to design expressive reduced models with efficient yet accurate force computations, without the need for training deformation examples. We demonstrate the application of our method to parametric models of human bodies, SMPL, and hands, MANO, with interactive simulations of contact with nonlinear soft-tissue deformation and skeletal response.>

show abstract

Section: Unposed Deformationmentioning

confidence: 93%

Section: Soft Skeletal Modelsmentioning

confidence: 99%

Section: Parametric Skeletal Modelmentioning

confidence: 99%

See 1 more Smart Citation

Parametric Skeletons with Reduced Soft‐Tissue Deformations

Tapia

Romero

Pérez

et al. 2021

Computer Graphics Forum

Self Cite

View full text Add to dashboard Cite

show abstract

“…Deul and Bender (2013) compute a simple layered model representing a bone, muscle, and fat layer, which they use for a multi-layered skinning approach. Simplistic layered models have also been used to extend the SMPL surface model (Loper et al, 2015) in order to support elastic effects in skinning animations (Kim et al, 2017;Romero et al, 2020). Compared to these works, our three layers yield an anatomically more accurate representation of the human body, while still being simpler and more efficient than complex irregular tetrahedralizations.…”

Section: Related Workmentioning

confidence: 99%

Inside Humans: Creating a Simple Layered Anatomical Model from Human Surface Scans

Komaritzan

Wenninger

Botsch

2021

Front. Virtual Real.

View full text Add to dashboard Cite

3D morphable models are widely used to describe the variation of human body shapes. However, these models typically focus on the surface of the human body, since the acquisition of the volumetric interior would require prohibitive medical imaging. In this paper we present a novel approach for creating a volumetric body template and for fitting this template to the surface scan of a person in a just a few seconds. The body model is composed of three surface layers for bones, muscles, and skin, which enclose the volumetric muscle and fat tissue in between them. Our approach includes a data-driven method for estimating the amount of muscle mass and fat mass from a surface scan, which provides more accurate fits to the variety of human body shapes compared to previous approaches. We also show how to efficiently embed fine-scale anatomical details, such as high resolution skeleton and muscle models, into the layered fit of a person. Our model can be used for physical simulation, statistical analysis, and anatomical visualization in computer animation and medical applications, which we demonstrate on several examples.

show abstract

“…Second, the avatar/model bodies during own-perceived body matching are usually presented either without clothing (e.g., De Coster et al, 2020 ) or with static clothing that does not provide additional cues (e.g., wrapping of different sizes of clothing around the body, movement of clothing when body moves) for body size estimation (e.g., Cornelissen et al, 2017 ; Mölbert et al, 2018 ; Thaler et al, 2018 ; Sadibolova et al, 2019 ). While it has been shown that dynamics play an important role in the perception of clothing ( Aliaga et al, 2015 ) and that observers are able to infer certain body properties (e.g., body stiffness) from clothing dynamics ( Romero et al, 2020 ), as well as the clothing’s mechanical properties ( Bi and Xiao, 2016 ), the question whether body size can be predicted by these dynamics and whether own-perceived body matching would be improved by these additional cues remain open questions. In sum, while movement and clothing dynamics likely play an important role in own-body perception in daily life, they have thus far not been investigated.…”

Section: Introductionmentioning

confidence: 99%

The Perceived Match Between Observed and Own Bodies, but Not Its Accuracy, Is Influenced by Movement Dynamics and Clothing Cues

Coster

Sánchez-Herrero²,

López‐Moreno

et al. 2021

Front. Hum. Neurosci.

View full text Add to dashboard Cite

Own-perceived body matching – the ability to match one’s own body with an observed body – is a difficult task for both general and clinical populations. Thus far, however, own-perceived body matching has been investigated in situations that are incongruent with how we are used to experience and perceive our body in daily life. In the current study, we aimed to examine own-perceived body matching in a context that more closely resembles real life. More specifically, we investigated the effects of body movement dynamics and clothing cues on own-perceived body matching. We asked participants to match their own body with an externally perceived body that was a 3D-generated avatar based on participants’ real bodies, fitted with a computer-generated dress. This perceived body was (1) either static (non-walking avatar) or dynamic (walking avatar), (2) either bigger, smaller, or the same size as participants’ own body size, and (3) fitted with a dress with a size either bigger, smaller, or the same as participants’ own dress size. Our results suggest that movement dynamics cues did not improve the accuracy of own-perceived body matching, but that confidence about dress fit was higher for dynamic avatars, and that the difference between dynamic and static avatars was dependent on participants’ self-esteem. Furthermore, when participants were asked to rate the observed body in reference to how they wanted to represent themselves to others, dynamic avatars were rated lower than static avatars for the biggest-sized bodies only, possibly reflecting the influence of movement cues on amplifying socio-cultural stereotypes. Finally, while smaller body/dress sizes were systematically rated higher than bigger body/dress sizes for several self-report items, the interplay between body and dress size played an important role in participants’ self-report as well. Thus, while our research suggests that movement and garment dynamics, allowing for realistic, concrete situations that are reminiscent of daily life, influence own-body perception, these cues did not lead to an improvement in accuracy. These findings provide important insights for research exploring (own-) body perception and bodily self-awareness, with practical (e.g., development of online avatars) and clinical (e.g., anorexia nervosa and body dysmorphic disorder) implications.

show abstract

Modeling and Estimation of Nonlinear Skin Mechanics for Animated Avatars

Cited by 16 publications

References 27 publications

Parametric Skeletons with Reduced Soft‐Tissue Deformations

Parametric Skeletons with Reduced Soft‐Tissue Deformations

Inside Humans: Creating a Simple Layered Anatomical Model from Human Surface Scans

The Perceived Match Between Observed and Own Bodies, but Not Its Accuracy, Is Influenced by Movement Dynamics and Clothing Cues

Contact Info

Product

Resources

About