Open AccessProceedings Article10.1145/2824840.2824850

Real-time variable rigidity texture mapping

- 24 Nov 2015

- pp 5

TL;DR: This paper introduces a technique that preserves the appearance of heterogeneous elasticity textures mapped on deforming surfaces by calculating dense, content-aware parameterisation warps in real-time.

Abstract: Parameterisation of models is typically generated for a single pose, the rest pose. When a model deforms, its parameterisation characteristics change, leading to distortions in the appearance of texture-mapped mesostructure. Such distortions are undesirable when the represented surface detail is heterogeneous in terms of elasticity (e.g. texture with skin and bone) as the material looks "rubbery". In this paper we introduce a technique that preserves the appearance of heterogeneous elasticity textures mapped on deforming surfaces by calculating dense, content-aware parameterisation warps in real-time. We demonstrate the usefulness of our method in a variety of scenarios: from application to production-quality assets, to real-time modelling previews and digital acting.

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In this paper the authors introduce a technique that preserves the appearance of heterogeneous elasticity textures mapped on deforming surfaces by calculating dense, content-aware parameterisation warps in realtime.. The authors demonstrate the usefulness of their method in a variety of scenarios: from application to production-quality assets, to realtime modelling previews and digital acting.

Table 1: Simulation times in milliseconds for various models. From left to right: (1) example model/animation name, (2) warp grid size, (3) Preprocessing time to generate rigity and warp mask hierarchies when any of the two changes and (4) time for simulation of the warp grid hierarchy. As it can be seen, preprocessing time depends purely on the size of the simulation grid. Also, it can be observed that above grid resolutions of 20482, performance drops significantly due to VRAM bottleneck.

Table 2: Rendering times (milliseconds). Columns 2 and 4 display the time required to render the scene, without and with applying the warp respectively. Column 3 shows the time required to invert the warp.

Figure 3: Comparison of our method with Thin Skin Elastodynamics [15] (sliding variant). The rest pose is on the left, TSE is in the middle and our method is on the right. As it can be seen, our method reduces distortions in a content-aware way, compared to global reduction of distortion in TSE. Our approach is also more stable in terms of animation; a video comparison is provided as additional material.

Figure 7: Example deformations for various datasets (Face2, Blowfish, T-Rex). The face and T-Rex textures contain stone/bone-like bumps which we wish to remain rigid. The blowfish has spikes mapped as displacement, which are marked as rigid. Uncorrected (red) and corrected (green) mapping of features are shown in (d). Corrected and uncorrected rigid features that overlap are displayed in yellow.

Figure 1: Rigid features on an animated face model. Zoomed-out view of an animated frame (a), authored rigid features shown in (c). The parameterisation is constant, so deforming from the rest pose (b) to an animation frame (d) compresses the features. Using our parameterisation warps, the shape and scale of the features are preserved (d).

Figure 4: Comparison of parameterisation methods using the MugJug model. The rest pose is the rightmost image; a mug. The deformed frames are shown from left to right: re-parameterisation using our method, Koniaris et al. [13], Sheffer and De Sturler[24], Mean Value Coordinates, and using the original UVs. Our method is the only one that preserves the features of the mug at the right scale. A video comparison is provided as additional material.

Citations

•Journal Article•10.1016/J.CAG.2020.07.006

Content-aware texture deformation with dynamic control

Geoffrey Guingo, +6 more

- 01 Oct 2020

- Computers & Graphics

TL;DR: A novel approach to model and control texture deformations, which is easy to implement in a standard graphics pipeline and controlled locally and dynamically by real-time integration along the streamlines of a pre-computed flow field.

...read moreread less

References

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Olga Sorkine, +1 more

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Michael S. Floater, +1 more

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TL;DR: Various concepts from differential geometry which are relevant to surface mapping are gathered and used to understand the strengths and weaknesses of the many methods for parameterizing piecewise linear surfaces and their relationship to one another.

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Matthias Müller, +3 more

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TL;DR: This paper presents an approach which omits the velocity layer as well and immediately works on the positions of the object and uses this approach to build a real time cloth simulator which is part of a physics software library for games.

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Journal Article•10.1109/MCG.1986.276672

Survey of Texture Mapping

Paul S. Heckbert

- 01 Aug 1986

TL;DR: The fundamentals of texture mapping are surveyed, which can be spilt into two topics: the geometric mapping that warps a texture onto a surface, and the filtering necessary to avoid aliasing.

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Book•10.1007/B138117

Advances in multiresolution for geometric modelling

Neil A. Dodgson, +2 more

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TL;DR: This paper presents an algorithm for Decomposing Multi-dimensional Non-manifold Objects into Nearly Manifold Components for Shape Reconstruction from Clouds of Points and discusses 3D Triangulations, Thinning, and Modelling.

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Real-time variable rigidity texture mapping

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Citations

Content-aware texture deformation with dynamic control

References

As-rigid-as-possible surface modeling

Surface Parameterization: a Tutorial and Survey

Position based dynamics

Survey of Texture Mapping

Advances in multiresolution for geometric modelling

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