EG 2021 - Short Papers

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https://diglib.eg.org/handle/10.2312/2633005

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Auto-rigging 3D Bipedal Characters in Arbitrary Poses
(The Eurographics Association, 2021) Kim, Jeonghwan; Son, Hyeontae; Bae, Jinseok; Kim, Young Min; Theisel, Holger and Wimmer, Michael
We present an end-to-end algorithm that can automatically rig a given 3D character such that it is ready for 3D animation. The animation of a virtual character requires the skeletal motion defined with bones and joints, and the corresponding deformation of the mesh represented with skin weights. While the conventional animation pipeline requires the initial 3D character to be in the predefined default pose, our pipeline can rig a 3D character in arbitrary pose. We handle the increased ambiguity by fixing the skeletal topology and solving for the full deformation space. After the skeletal positions and orientations are fully discovered, we can deform the provided 3D character into the default pose, from which we can animate the character with the help of recent motion-retargeting techniques. Our results show that we can successfully animate initially deformed characters, which was not possible with previous works.
Automatic Hierarchical Arrangement of Vector Designs
(The Eurographics Association, 2021) Fisher, Matthew; Agarwal, Vineet; Beri, Tarun; Theisel, Holger and Wimmer, Michael
We present a method that transforms an unstructured vector design into a logical hierarchy of groups of objects. Each group is a meaningful collection, formed by proximity in visual characteristics (like size, shape, color, etc.) and spatial location of objects and models the grouping principles designers use. We first simplify the input design by partially or completely flattening it and isolate duplicate geometries in the design (for example, repeating patterns due to copy and paste operations). Next we build the object containment hierarchy by assigning objects that are wholly enclosed inside the geometry of other objects as children of the enclosing parent. In the final clustering phase, we use agglomerative clustering to obtain a bottom-up hierarchical grouping of all objects by comparing and ranking all pairs of objects according to visual and spatial characteristics. Spatial proximity segregates far apart objects, but when they are identical (or near identical) designers generally prefer to keep (and edit) them together. To accommodate this, we detect near identical objects and group them together during clustering despite their spatial separation. We further restrict group formation so that z-order disturbances in the design keep the visual appearance unaffected for tightly-overlapping geometry. The generated organization is equivalent to the original design and the organization results are used to facilitate abstract navigation (hierarchical, lateral or near similar) and selections in the design. Our technique works well with a variety of input designs with commonly identifiable objects and structural patterns.
Bregman Approach to Single Image De-Raining
(The Eurographics Association, 2021) Szirmay-Kalos, Laszlo; Tóth, Márton; Theisel, Holger and Wimmer, Michael
Surveillance cameras are expected to work also in bad visibility conditions, which requires algorithmic solutions to improve the captured image and to eliminate image degradation caused by these weather conditions. Algorithms for such tasks belong to the field of computational photography and have been successful in eliminating haze, fog, motion blur, etc. This paper presents a simple algorithm to suppress rain or snow from single images. The algorithm uses energy minimization, and we propose a novel data term and a Bregman distance based regularization term reflecting the particular properties of precipitation.
Data-driven Garment Pattern Estimation from 3D Geometries
(The Eurographics Association, 2021) Goto, Chihiro; Umetani, Nobuyuki; Theisel, Holger and Wimmer, Michael
Three-dimensional scanning technology recently becomes widely available to the public. However, it is difficult to simulate clothing deformation from the scanned people because scanned data lacks information required for the clothing simulation. In this paper, we present a technique to estimate clothing patterns from a scanned person in cloth. Our technique uses image-based deep learning to estimate the type of pattern on the projected image. The key contribution is converting image-based inference into three-dimensional clothing pattern estimation. We evaluate our technique by applying our technique to an actual scan.
EUROGRAPHICS 2021: Short Papers Frontmatter
(Eurographics Association, 2021) Theisel, Holger; Wimmer, Michael; Theisel, Holger and Wimmer, Michael
Gaming in Elliptic Geometry
(The Eurographics Association, 2021) Szirmay-Kalos, Laszlo; Magdics, Milán; Theisel, Holger and Wimmer, Michael
An interesting way to explore curved spaces is to play games governed by the rules of non-Euclidean geometries. However, modeling tools and game engines are developed with Euclidean geometry in mind. This paper addresses the problem of porting a game from Euclidean to elliptic geometry. We consider primarily the geometric calculations and the transformation pipeline.
Interactive Finite Element Model of Needle Insertion and Laceration
(The Eurographics Association, 2021) Perrusi, Pedro Henrique Suruagy; Baksic, Paul; Courtecuisse, Hadrien; Theisel, Holger and Wimmer, Michael
This paper introduces an interactive model of needle insertion, including the possibility to simulate lacerations of tissue around the needle. The method relies on complementary constraints to couple the Finite Element models of the needle and tissue. The cutting path is generated from mechanical criteria (i.e. cutting force) at arbitrary resolution, avoiding expensive remeshing of Finite Element meshes. Complex behavior can be simulated in real time such as friction along the shaft of the needle, puncture and cutting force resulting from interactions of the needle with the tissue. The method is illustrated both in an interactive simulation of a needle insertion/cutting and in a robotic needle insertion in liver tissue during the breathing motion.
Interactive Simulation for easy Decision-making in Fluid Dynamics
(The Eurographics Association, 2021) Wang, Mengchen; Férey, Nicolas; Magoulès, Frédéric; Bourdot, Patrick; Theisel, Holger and Wimmer, Michael
A conventional study of fluid simulation involves different stages including conception, simulation, visualization, and analysis tasks. It is, therefore, necessary to switch between different software and interactive contexts which implies costly data manipulation and increases the time needed for decision making. Our interactive simulation approach was designed to shorten this loop, allowing users to visualize and steer a simulation in progress without waiting for the end of the simulation. The methodology allows the users to control, start, pause, or stop a simulation in progress, to change global physical parameters, to interact with its 3D environment by editing boundary conditions such as walls or obstacles. This approach is made possible by using a methodology such as the Lattice Boltzmann Method (LBM) to achieve interactive time while remaining physically relevant. In this work, we present our platform dedicated to interactive fluid simulation based on LBM. The contribution of our interactive simulation approach to decision making will be evaluated in a study based on a simple but realistic use case.
Interactive Synthesis of 3D Geometries of Blood Vessels
(The Eurographics Association, 2021) Rauch, Nikolaus; Harders, Matthias; Theisel, Holger and Wimmer, Michael
In surgical training simulators, where various organ surfaces make up the majority of the scene, the visual appearance is highly dependent on the quality of the surface textures. Blood vessels are an important detail in this; they need to be incorporated into an organ's texture. Moreover, the actual blood vessel geometries also have to be part of the simulated surgical procedure itself, e.g. during cutting. Since the manual creation of vessel geometry or branching details on textures is highly tedious, an automatic synthesis technique capable of generating a wide range of blood vessel patterns is needed.We propose a new synthesis approach based on the space colonization algorithm. As extension, physiological constraints on the proliferation of branches are enforced to create realistic vascular structures. Our framework is capable of generating three-dimensional blood vessel networks in a matter of milliseconds, thus allowing a 3D modeller to tweak parameters in real-time to obtain a desired appearance.
Modeling and Actuation of Cable-driven Silicone Soft Robots
(The Eurographics Association, 2021) Frâncu, Mihail; Theisel, Holger and Wimmer, Michael
In this paper we present a framework for modeling cable-driven soft robots fabricated from silicone rubber - an incompressible material. Our forward simulation model can use either the standard or the mixed formulation of the finite element method (FEM). The latter prevents volumetric locking for incompressible materials and is more accurate for low resolution meshes. Hence, we show that mixed FEM is well suited for estimating elastic parameters and simulator validation. We also introduce a cable actuation model using barycentric coordinates and then use it to solve some simple control problems.
Ray Tracing Lossy Compressed Grid Primitives
(The Eurographics Association, 2021) Benthin, Carsten; Vaidyanathan, Karthik; Woop, Sven; Theisel, Holger and Wimmer, Michael
We propose a new watertight representation of geometry for ray tracing highly complex scenes in a memory efficient manner. Polygon meshes in the scene are first converted into compressed grid primitives, which are represented by a base bilinear patch with quantized displacement vectors. Ray-scene intersections are then computed by efficiently decompressing these grids onthe- fly and intersecting the implicit triangles. Our representation requires just 5:4??6:6 bytes per triangle for the combined geometry and acceleration structure, resulting in a 5-7x reduction in memory footprint compared to indexed triangle meshes. This is achieved with less than 15% increase in rendering time.
Robust Image Denoising using Kernel Predicting Networks
(The Eurographics Association, 2021) Cai, Zhilin; Zhang, Yang; Manzi, Marco; Oztireli, Cengiz; Gross, Markus; Aydin, Tunç Ozan; Theisel, Holger and Wimmer, Michael
We present a new method for designing high quality denoisers that are robust to varying noise characteristics of input images. Instead of taking a conventional blind denoising approach or relying on explicit noise parameter estimation networks as well as invertible camera imaging pipeline models, we propose a two-stage model that first processes an input image with a small set of specialized denoisers, and then passes the resulting intermediate denoised images to a kernel predicting network that estimates per-pixel denoising kernels. We demonstrate that our approach achieves robustness to noise parameters at a level that exceeds comparable blind denoisers, while also coming close to state-of-the-art denoising quality for camera sensor noise.
SoftWalks: Real-Time, Two-Ways Interaction between a Character and Loose Grounds
(The Eurographics Association, 2021) Paliard, Chloé; Alvarado, Eduardo; Rohmer, Damien; Cani, Marie-Paule; Theisel, Holger and Wimmer, Michael
When walking on loose terrains, possibly covered with vegetation, the ground and grass should deform, but the character's gait should also change accordingly.We propose a method for modeling such two-ways interactions in real-time.We first complement a layered character model by a high-level controller, which uses position and angular velocity inputs to improve dynamic oscillations when walking on various slopes. Secondly, at a refined level, the feet are set to locally deform the ground and surrounding vegetation using efficient procedural functions, while the character's response to such deformations is computed through adapted inverse kinematics. While simple to set up, our method is generic enough to adapt to any character morphology. Moreover, its ability to generate in real time, consistent gaits on a variety of loose grounds of arbitrary slope, possibly covered with grass, makes it an interesting solution to enhance films and games.
Tight Normal Cone Merging for Efficient Collision Detection of Thin Deformable Objects
(The Eurographics Association, 2021) Han, Dong-Hoon; Lee, Chang-Jin; Lee, Sangbin; Ko, Hyeong-Seok; Theisel, Holger and Wimmer, Michael
When simulating thin deformable objects such as clothes, collision detection alone takes a lot of computation. One way of reducing the computation is culling false-positives as much as possible. In the context of bounding volume hierarchy, Provot proposed a culling method that is based on hierarchical merging of normal enclosing cones. In this work, we investigate Provot's merging algorithm and show that there is some room for improvement. We propose a new merging algorithm, in the context of discrete collision detection, which always produces an equal or tighter mergence than Provot's merging. We extend the above algorithm so that it can be used in the context of continuous collision detection. Experiments show that the proposed method makes about 25% reduction in the number of triangle pairs for which vertex-triangle or edge-edge collision test has to be performed, and 18% reduction in time for collision detection.
Visual Analysis of Point Cloud Neighborhoods via Multi-Scale Geometric Measures
(The Eurographics Association, 2021) Ritter, Marcel; Schiffner, Daniel; Harders, Matthias; Theisel, Holger and Wimmer, Michael
Point sets are a widely used spatial data structure in computational and observational domains, e.g. in physics particle simulations, computer graphics or remote sensing. Algorithms typically operate in local neighborhoods of point sets, for computing physical states, surface reconstructions, etc. We present a visualization technique based on multi-scale geometric features of such point clouds. We explore properties of different choices on the underlying weighted co-variance neighborhood descriptor, illustrated on different point set geometries and for varying noise levels. The impact of different weighting functions and tensor centroids, as well as point set features and noise levels becomes visible in the rotation-invariant feature images. We compare to a curvature based scale space visualization method and, finally, show how features in real-world LiDAR data can be inspected by images created with our approach in an interactive tool. In contrast to the curvature based approach, with our method line structures are highlighted over growing scales, with clear border regions to planar or spherical geometric structures.
Visualising the Transition of Large Networks via Dimensionality Reduction to Illustrate the Evolution of the Human Brain
(The Eurographics Association, 2021) Ganglberger, Florian; Kaczanowska, Joanna; Haubensak, Wulf; Bühler, Katja; Theisel, Holger and Wimmer, Michael
Advances in high-throughput imaging techniques enable the creation of networks depicting spatio-temporal biological and neurophysiological processes with unprecedented size and magnitude. These networks involve thousands of nodes, which can not be compared over time by traditional methods due to complexity and clutter. When investigating networks over multiple time steps, a crucial question for the visualisation research community becomes apparent: How to visually trace changes of the connectivity over several transitions? Therefore, we developed an easy-to-use method that maps multiple networks to a common embedding space. Visualising the distribution of node-clusters of interest (e.g. brain regions) enables their tracing over time. We demonstrate this approach by visualizing spatial co-evolution networks of different evolutionary timepoints as small multiples to investigate how the human brain genetically and functionally evolved over the mammalian lineage.
Visualizing Errors in Rendered High Dynamic Range Images
(The Eurographics Association, 2021) Andersson, Pontus; Nilsson, Jim; Shirley, Peter; Akenine-Möller, Tomas; Theisel, Holger and Wimmer, Michael
A new error metric targeting rendered high dynamic range images is presented. Our method computes a composite visualization over a number of low dynamic range error maps of exposure compensated and tone mapped image pairs with automatically computed, or manually provided, parameters. We argue that our new error maps predict errors substantially better than metrics previously used in rendering. Source code is released with the hope that our work can be a useful tool for future research.

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