IA Scholar Query: Tesselations by Connection in Orders.
https://scholar.archive.org/
Internet Archive Scholar query results feedeninfo@archive.orgSat, 31 Dec 2022 00:00:00 GMTfatcat-scholarhttps://scholar.archive.org/help1440Preface
https://scholar.archive.org/work/dujjq2py4rc7xp4kp6epptgsz4
Books leave more unsaid than said; more to be imagined than to be read; more in the wholly created than in the created. I began the work that in time became this book, as Heidegger might say, as a wanderer along a path rather than a focused and directed researcher. An opportunity arose and fieldwork ensued in an available and convivial police department; I transferred my interest to the Metropolitan Washington Department, moved to Boston, and walked across the street to the BPD. The uncritical and rather naïve idea that crime mapping-in-use was the cause of a crime drop arose during the course of the study and was neither the impetus to nor the result of my research. The axial and organizing idea that there are several contesting rationalities, and not just one-modes in which we relate to the world of others-emerged over the course of the study. I assumed initially that crime mapping (CM) and crime analyzing (CA) is a "technological package," a means by which work is accomplished, that has symbolic (the way it is represented and thought about-its meaning) and instrumental (what work it actually does where and when) facets. However, while it is that, a pragmatic tool, it is above all a stimulus to systematic imagining. As the work unfolded I narrowed my interest to the way, in a traditionally structured organization, social change emerges. I called the organization the music and the practices, some of which changed, the dance. Because organizations rationalize all that they do and do what they know how to do, they treasure institutional accounts, or explanations for why what is done is that which best accomplishes what they set out to do. Such tautologies are powerful. Technology stimulates; it mediates relationships and elaborates complexity. It can disrupt power balances. Technology produces new social objects, and information technology in particular reflects upon itself, creating reflective loops and conundrums. Social objects produced by information technology, crime maps and their impedimenta, can be made real to police-lasting, ixwork_dujjq2py4rc7xp4kp6epptgsz4Sat, 31 Dec 2022 00:00:00 GMTSimulating hyperbolic space on a circuit board
https://scholar.archive.org/work/l3szjt56tnclffwqvd7eazmkwa
The Laplace operator encodes the behavior of physical systems at vastly different scales, describing heat flow, fluids, as well as electric, gravitational, and quantum fields. A key input for the Laplace equation is the curvature of space. Here we discuss and experimentally demonstrate that the spectral ordering of Laplacian eigenstates for hyperbolic (negatively curved) and flat two-dimensional spaces has a universally different structure. We use a lattice regularization of hyperbolic space in an electric-circuit network to measure the eigenstates of a 'hyperbolic drum', and in a time-resolved experiment we verify signal propagation along the curved geodesics. Our experiments showcase both a versatile platform to emulate hyperbolic lattices in tabletop experiments, and a set of methods to verify the effective hyperbolic metric in this and other platforms. The presented techniques can be utilized to explore novel aspects of both classical and quantum dynamics in negatively curved spaces, and to realise the emerging models of topological hyperbolic matter.Patrick M Lenggenhager, Alexander Stegmaier, Lavi K Upreti, Tobias Hofmann, Tobias Helbig, Achim Vollhardt, Martin Greiter, Ching Hua Lee, Stefan Imhof, Hauke Brand, Tobias Kießling, Igor Boettcher, Titus Neupert, Ronny Thomale, Tomáš Bzdušekwork_l3szjt56tnclffwqvd7eazmkwaThu, 01 Dec 2022 00:00:00 GMTAccess Journal Volume 02, Number 03
https://scholar.archive.org/work/keh5bvanyrh5ths3uzlqnh4xaa
ACCESS (Adoption of Contemporary research Concentrating Education Science & Social Studies) Journal is an initiative of GEIST International Foundation where it invites researchers, enthusiasts, experts, teachers, educators, faculty members, policy makers, journalists and regulators and students of the education sector from the different parts of the world share their research experiences and results on education, educational development, teaching methodologies, innovation, trends and future. GEIST International Foundation welcomes honorable contributors from the global education sector to submit their research and study contents so that this journal can become a platform for knowledge and experience give-and-take.GEIST International Foundationwork_keh5bvanyrh5ths3uzlqnh4xaaTue, 01 Nov 2022 00:00:00 GMTVAST: the Void Analysis Software Toolkit
https://scholar.archive.org/work/2674afnqq5bq7nkbmkvc222254
Voids are expansive regions in the universe containing significantly fewer galaxies than surrounding galaxy clusters and filaments. They are a fundamental feature of the cosmic web and provide important information about galaxy physics and cosmology. For example, correlations between voids and luminous tracers of large-scale structure improve constraints on the expansion of the universe as compared to using tracers alone, and numerous studies have shown that the void environment influences the evolution of galaxies. However, what constitutes a void is vague and formulating a concrete definition to use in a void-finding algorithm is not trivial. As a result, several different algorithms exist to identify these cosmic underdensities. Our Void Analysis Software Toolkit, or VAST, provides Python 3 implementations of two such algorithms: VoidFinder and V 2 . This consolidation of two popular void-finding algorithms allows the user to, for example, easily compare the results of their analysis using different void definitions.Kelly A. Douglass, Dahlia Veyrat, Stephen W. O'Neill Jr., Segev BenZvi, Fatima Zaidouni, Michaela Guzzettiwork_2674afnqq5bq7nkbmkvc222254Thu, 29 Sep 2022 00:00:00 GMTOptimal independent generating system for the congruence subgroups Γ_0(p)
https://scholar.archive.org/work/q254pmqhbffipk62zgc6sahfzy
For a prime p>3 we prove that the congruence subgroup Γ_0(p) admits a free product decomposition into cyclic factors in such a way that the (2,1)–component of each cyclic generator is either p or 0; we can further require that the Frobenius norm of each generator is less than 2p. We establish this by showing that the cusp set of some special (fundamental) polygon for Γ_0(p) is between the extended Farey sequences F_v^* of order v:=⌊√(p)⌋ and F_w^* of order w:=⌊√(4p/3)⌋. As a byproduct, we obtain a geometric proof of an estimate for ∑_i=1^vϕ(i). We also exhibit a complete finite list of the primes p for which the cusp sets coincide with F_v^*. We finally give an arithmetic characterization of the primes p for which the largest denominator among the cusps is exactly w; the list of such primes is expected to be infinite by a weak form of the Bunyakovsky conjecture.Nhat Minh Doan, Sang-hyun Kim, Mong Lung Lang, Ser Peow Tanwork_q254pmqhbffipk62zgc6sahfzyWed, 28 Sep 2022 00:00:00 GMTHomological- and analytical-preserving serendipity framework for polytopal complexes, with application to the DDR method
https://scholar.archive.org/work/fa2jy35znzeajipmki63npwc7i
In this work we investigate from a broad perspective the reduction of degrees of freedom through serendipity techniques for polytopal methods compatible with Hilbert complexes. We first establish an abstract framework that, given two complexes connected by graded maps, identifies a set of properties enabling the transfer of the homological and analytical properties from one complex to the other. This abstract framework is designed having in mind discrete complexes, with one of them being a reduced version of the other, such as occurring when applying serendipity techniques to numerical methods. We then use this framework as an overarching blueprint to design a serendipity DDR complex. Thanks to the combined use of higher-order reconstructions and serendipity, this complex compares favorably in terms of degrees of freedom (DOF) count to all the other polytopal methods previously introduced and also to finite elements on certain element geometries. The gain resulting from such a reduction in the number of DOFs is numerically evaluated on two model problems: a magnetostatic model, and the Stokes equations.Daniele A. Di Pietro, Jérôme Droniouwork_fa2jy35znzeajipmki63npwc7iWed, 28 Sep 2022 00:00:00 GMTLine Segment Tracking in the HL-LHC
https://scholar.archive.org/work/jw23566elfa2tna5fogmg5izqy
The major challenge posed by the high instantaneous luminosity in the High Luminosity LHC (HL-LHC) motivates efficient and fast reconstruction of charged particle tracks in a high pile-up environment. While there have been efforts to use modern techniques like vectorization to improve the existing classic Kalman Filter based reconstruction algorithms, Line Segment Tracking takes a fundamentally different approach by doing a bottom-up reconstruction of tracks. Small track stubs from adjoining detector regions are constructed, and then these track stubs that are consistent with typical track trajectories are successively linked. Since the production of these track stubs is localized, they can be made in parallel, which lends way into using architectures like GPUs and multi-CPUs to take advantage of the parallelism. The algorithm is implemented in the context of the CMS Phase-2 Tracker and runs on NVIDIA Tesla V100 GPUs. Good physics and timing performance has been obtained, and stepping stones for the future are elaborated.Gavin Niendorf, Tres Reid, Peter Wittich, Peter Elmer, Bei Wang, Philip Chang, Yanxi Gu, Vyacheslav Krutelyov, Balaji Venkat Sathia Narayanan, Matevz Tadel, Emmanouil Vourliotis, Avi Yagilwork_jw23566elfa2tna5fogmg5izqyWed, 28 Sep 2022 00:00:00 GMTData-driven Efficient Solvers for Langevin Dynamics on Manifold in High Dimensions
https://scholar.archive.org/work/5q7phfngmjgnnjnxcegphp3rg4
We study the Langevin dynamics of a physical system with manifold structure ℳ⊂ℝ^p based on collected sample points {𝗑_i}_i=1^n ⊂ℳ that probe the unknown manifold ℳ. Through the diffusion map, we first learn the reaction coordinates {𝗒_i}_i=1^n⊂𝒩 corresponding to {𝗑_i}_i=1^n, where 𝒩 is a manifold diffeomorphic to ℳ and isometrically embedded in ℝ^ℓ with ℓ≪ p. The induced Langevin dynamics on 𝒩 in terms of the reaction coordinates captures the slow time scale dynamics such as conformational changes in biochemical reactions. To construct an efficient and stable approximation for the Langevin dynamics on 𝒩, we leverage the corresponding Fokker-Planck equation on the manifold 𝒩 in terms of the reaction coordinates 𝗒. We propose an implementable, unconditionally stable, data-driven finite volume scheme for this Fokker-Planck equation, which automatically incorporates the manifold structure of 𝒩. Furthermore, we provide a weighted L^2 convergence analysis of the finite volume scheme to the Fokker-Planck equation on 𝒩. The proposed finite volume scheme leads to a Markov chain on {𝗒_i}_i=1^n with an approximated transition probability and jump rate between the nearest neighbor points. After an unconditionally stable explicit time discretization, the data-driven finite volume scheme gives an approximated Markov process for the Langevin dynamics on 𝒩 and the approximated Markov process enjoys detailed balance, ergodicity, and other good properties.Yuan Gao, Jian-Guo Liu, Nan Wuwork_5q7phfngmjgnnjnxcegphp3rg4Tue, 27 Sep 2022 00:00:00 GMTPersistent homology based goodness-of-fit tests for spatial tessellations
https://scholar.archive.org/work/3ogyb6yebng5nhf2fgixp275ki
Motivated by the rapidly increasing relevance of virtual material design in the domain of materials science, it has become essential to assess whether topological properties of stochastic models for a spatial tessellation are in accordance with a given dataset. Recently, tools from topological data analysis such as the persistence diagram have allowed to reach profound insights in a variety of application contexts. In this work, we establish the asymptotic normality of a variety of test statistics derived from a tessellation-adapted refinement of the persistence diagram. Since in applications, it is common to work with tessellation data subject to interactions, we establish our main results for Voronoi and Laguerre tessellations whose generators form a Gibbs point process. We elucidate how these conceptual results can be used to derive goodness of fit tests, and then investigate their power in a simulation study. Finally, we apply our testing methodology to a tessellation describing real foam data.Christian Hirsch, Johannes Krebs, Claudia Redenbachwork_3ogyb6yebng5nhf2fgixp275kiTue, 27 Sep 2022 00:00:00 GMTSignatures of noncommutative inspired black holes from exponential corrections to the black hole entropy and the Smarr formula
https://scholar.archive.org/work/fcmt2dbq55eoleyceeavaulks4
It has been recently shown in [\href{https://link.aps.org/doi/10.1103/PhysRevLett.125.041302}{Phys. Rev. Lett. 125 (2020) 041302}] that microstate counting carried out for quantum states residing on the horizon of a black hole leads to a correction of the form $\exp(-A/4l_p^2)$ in the Bekenstein-Hawking form of the black hole entropy. In this letter we develop a novel approach to obtain the possible form of the spacetime geometry from the entropy of the black hole for a given horizon radius. The uniqueness of this solution for a given energy-momentum tensor has also been discussed. Remarkably, the black hole geometry reconstructed has striking similarities to that of noncommutative inspired Schwarzschild black holes [\href{https://www.sciencedirect.com/science/article/pii/S0370269305016126}{Phys. Lett. B 632 (2006) 547}]. We also obtain the matter density functions using the Einstein's field equations for the geometries we reconstruct from thermodynamics of black holes. These also have similarities to that of the matter density function of a noncommutative inspired Schwarzschild black hole. We finally compute the Komar energy and the Smarr formula for the effective black hole geometry and compare it with that of the noncommutative inspired Schwarzschild black hole. We also discuss some astrophysical implications of the solutions.Soham Sen, Ashis Saha, Sunandan Gangopadhyaywork_fcmt2dbq55eoleyceeavaulks4Tue, 27 Sep 2022 00:00:00 GMTForecasting the success of the WEAVE Wide-Field Cluster Survey on the extraction of the cosmic web filaments around galaxy clusters
https://scholar.archive.org/work/7wy5nqbv4zgjda2tcxp23mwbja
Next-generation wide-field spectroscopic surveys will observe the infall regions around large numbers of galaxy clusters with high sampling rates for the first time. Here we assess the feasibility of extracting the large-scale cosmic web around clusters using forthcoming observations, given realistic observational constraints. We use a sample of 324 hydrodynamic zoom-in simulations of massive galaxy clusters from TheThreeHundred project to create a mock-observational catalogue spanning 5R_200 around 160 analogue clusters. These analogues are matched in mass to the 16 clusters targetted by the forthcoming WEAVE Wide-Field Cluster Survey (WWFCS). We consider the effects of the fibre allocation algorithm on our sampling completeness and find that we successfully allocate targets to 81.7 %± 1.3 of the members in the cluster outskirts. We next test the robustness of the filament extraction algorithm by using a metric, D_skel, which quantifies the distance to the filament spine. We find that the median positional offset between reference and recovered filament networks is D_skel = 0.13 ± 0.02 Mpc, much smaller than the typical filament radius of ∼ 1 Mpc. Cluster connectivity of the recovered network is not substantially affected. Our findings give confidence that the WWFCS will be able to reliably trace cosmic web filaments in the vicinity around massive clusters, forming the basis of environmental studies into the effects of pre-processing on galaxy evolution.Daniel J. Cornwell, Ulrike Kuchner, Alfonso Aragón-Salamanca, Meghan E. Gray, Frazer R. Pearce, J. Alfonso L. Aguerri, Weiguang Cui, J. Méndez-Abreu, Luis Peralta de Arriba, Scott C. Tragerwork_7wy5nqbv4zgjda2tcxp23mwbjaTue, 27 Sep 2022 00:00:00 GMTSuperiority of GNN over NN in generalizing bandlimited functions
https://scholar.archive.org/work/r76iqls5vvea5kerfycmmlmsuy
We constructively show, via rigorous mathematical arguments, that GNN architectures outperform those of NN in approximating bandlimited functions on compact d-dimensional Euclidean grids. We show that the former only need ℳ sampled functional values in order to achieve a uniform approximation error of O_d(2^-ℳ^1/d) and that this error rate is optimal, in the sense that, NNs might achieve worse.A. Martina Neuman, Rongrong Wang, Yuying Xiework_r76iqls5vvea5kerfycmmlmsuyTue, 27 Sep 2022 00:00:00 GMTIncreased Extrasynaptic Glutamate Escape in Stochastically Shaped Probabilistic Synaptic Environment
https://scholar.archive.org/work/lebhbmnwdzea3d3g5xyzxlivf4
Excitatory synapses in the brain are often surrounded by nanoscopic astroglial processes that express high-affinity glutamate transporters at a high surface density. This ensures that the bulk of glutamate leaving the synaptic cleft is taken up for its subsequent metabolic conversion and replenishment in neurons. Furthermore, variations in the astroglial coverage of synapses can thus determine to what extent glutamate released into the synaptic cleft could activate its receptors outside the cleft. The biophysical determinants of extrasynaptic glutamate actions are complex because they involve a competition between transporters and target receptors of glutamate in the tortuous space of synaptic environment. To understand key spatiotemporal relationships between the extrasynaptic landscapes of bound and free glutamate, we explored a detailed Monte Carlo model for its release, diffusion, and uptake. We implemented a novel representation of brain neuropil in silico as a space filled with randomly scattered, overlapping spheres (spheroids) of distributed size. The parameters of perisynaptic space, astroglial presence, and glutamate transport were constrained by the empirical data obtained for the 'average' environment of common cortical synapses. Our simulations provide a glimpse of the perisynaptic concentration landscapes of free and transporter-bound glutamate relationship, suggesting a significant tail of space-average free glutamate within 3 ms post-release.Leonid P. Savtchenko, Dmitri A. Rusakovwork_lebhbmnwdzea3d3g5xyzxlivf4Mon, 26 Sep 2022 00:00:00 GMTHolographic measurement and bulk teleportation
https://scholar.archive.org/work/yvdlqn5rhbcs5dgihimjexx7t4
Holography has taught us that spacetime is emergent and its properties depend on the entanglement structure of the dual theory. In this paper, we describe how changes in the entanglement due to a local projective measurement (LPM) on a subregion A of the boundary theory modify the bulk dual spacetime. We find that LPMs destroy portions of the bulk geometry, yielding post-measurement bulk spacetimes dual to the complementary unmeasured region A^c that are cut off by end-of-the-world branes. Using a bulk calculation in AdS_3 and tensor network models of holography, we show that the portions of the bulk geometry that are preserved after the measurement depend on the size of A and the state we project onto. The post-measurement bulk dual to A^c includes regions that were originally part of the entanglement wedge of A prior to measurement. This suggests that LPMs performed on a boundary subregion A teleport part of the bulk information originally encoded in A into the complementary region A^c. In semiclassical holography an arbitrary amount of bulk information can be teleported in this way, while in tensor network models the teleported information is upper-bounded by the amount of entanglement shared between A and A^c due to finite-N effects. When A is the union of two disjoint subregions, the measurement triggers an entangled/disentangled phase transition between the remaining two unmeasured subregions, corresponding to a connected/disconnected phase transition in the bulk description. Our results shed new light on the effects of measurement on the entanglement structure of holographic theories and give insight on how bulk information can be manipulated from the boundary theory. They could also be extended to more general quantum systems and tested experimentally, and represent a first step towards a holographic description of measurement-induced phase transitions.Stefano Antonini, Gregory Bentsen, ChunJun Cao, Jonathan Harper, Shao-Kai Jian, Brian Swinglework_yvdlqn5rhbcs5dgihimjexx7t4Mon, 26 Sep 2022 00:00:00 GMTReconstructing Compact Building Models from Point Clouds Using Deep Implicit Fields
https://scholar.archive.org/work/ipm4dqtvafh3fpjswsqagundjy
While three-dimensional (3D) building models play an increasingly pivotal role in many real-world applications, obtaining a compact representation of buildings remains an open problem. In this paper, we present a novel framework for reconstructing compact, watertight, polygonal building models from point clouds. Our framework comprises three components: (a) a cell complex is generated via adaptive space partitioning that provides a polyhedral embedding as the candidate set; (b) an implicit field is learned by a deep neural network that facilitates building occupancy estimation; (c) a Markov random field is formulated to extract the outer surface of a building via combinatorial optimization. We evaluate and compare our method with state-of-the-art methods in generic reconstruction, model-based reconstruction, geometry simplification, and primitive assembly. Experiments on both synthetic and real-world point clouds have demonstrated that, with our neural-guided strategy, high-quality building models can be obtained with significant advantages in fidelity, compactness, and computational efficiency. Our method also shows robustness to noise and insufficient measurements, and it can directly generalize from synthetic scans to real-world measurements. The source code of this work is freely available at https://github.com/chenzhaiyu/points2poly.Zhaiyu Chen, Hugo Ledoux, Seyran Khademi, Liangliang Nanwork_ipm4dqtvafh3fpjswsqagundjyMon, 26 Sep 2022 00:00:00 GMTGraph Neural Networks for Multi-Robot Active Information Acquisition
https://scholar.archive.org/work/tvfk3rtoejgqjiat7s4v23xefa
This paper addresses the Multi-Robot Active Information Acquisition (AIA) problem, where a team of mobile robots, communicating through an underlying graph, estimates a hidden state expressing a phenomenon of interest. Applications like target tracking, coverage and SLAM can be expressed in this framework. Existing approaches, though, are either not scalable, unable to handle dynamic phenomena or not robust to changes in the communication graph. To counter these shortcomings, we propose an Information-aware Graph Block Network (I-GBNet), an AIA adaptation of Graph Neural Networks, that aggregates information over the graph representation and provides sequential-decision making in a distributed manner. The I-GBNet, trained via imitation learning with a centralized sampling-based expert solver, exhibits permutation equivariance and time invariance, while harnessing the superior scalability, robustness and generalizability to previously unseen environments and robot configurations. Experiments on significantly larger graphs and dimensionality of the hidden state and more complex environments than those seen in training validate the properties of the proposed architecture and its efficacy in the application of localization and tracking of dynamic targets.Mariliza Tzes, Nikolaos Bousias, Evangelos Chatzipantazis, George J. Pappaswork_tvfk3rtoejgqjiat7s4v23xefaSat, 24 Sep 2022 00:00:00 GMTA Convolution-Based Computational Technique for Subdivision Depth of Doo-Sabin Subdivision Surface
https://scholar.archive.org/work/ypnryhyrondsja2ddrz37aehoa
Subdivision surface schemes are used to produce smooth shapes, which are applied for modelling in computer-aided geometric design. In this paper, a new and efficient numerical technique is presented to estimate the error bound and subdivision depth of the uniform Doo-Sabin subdivision scheme. In this technique, first, a result for computing bounds between P k (a polygon at k th level) and P ∞ (limit surface) of the Doo-Sabin scheme is obtained. After this, subdivision depth (the number of iterations) is computed by using the user-defined error tolerance. In addition, the results of the proposed technique are verified by taking distinct valence numbers of the Doo-Sabin surface scheme.Faheem Khan, Bushra Shakoor, Ghulam Mustafa, Sidra Razaq, R. U. Gobithaasanwork_ypnryhyrondsja2ddrz37aehoaSat, 24 Sep 2022 00:00:00 GMTAn extension to VORO++ for multithreaded computation of Voronoi cells
https://scholar.archive.org/work/7rr7ozdtafg5hpu2clyg4fapba
VORO++ is a software library written in C++ for computing the Voronoi tessellation, a technique in computational geometry that is widely used for analyzing systems of particles. VORO++ was released in 2009 and is based on computing the Voronoi cell for each particle individually. Here, we take advantage of modern computer hardware, and extend the original serial version to allow for multithreaded computation of Voronoi cells via the OpenMP application programming interface. We test the performance of the code, and demonstrate that we can achieve parallel efficiencies greater than 95% in many cases. The multithreaded extension follows standard OpenMP programming paradigms, allowing it to be incorporated into other programs. We provide an example of this using the VoroTop software library, performing a multithreaded Voronoi cell topology analysis of up to 102.4 million particles.Jiayin Lu, Emanuel A. Lazar, Chris H. Rycroftwork_7rr7ozdtafg5hpu2clyg4fapbaFri, 23 Sep 2022 00:00:00 GMTCreating Compact Regions of Social Determinants of Health
https://scholar.archive.org/work/urcsxl74k5atjpohdgrhdqhbuu
Regionalization is the act of breaking a dataset into contiguous homogeneous regions that are heterogeneous from each other. Many different algorithms exist for performing regionalization; however, using these algorithms on large real world data sets have only become feasible in terms of compute power in recent years. Very few studies have been done comparing different regionalization methods, and those that do lack analysis in memory, scalability, geographic metrics, and large-scale real-world applications. This study compares state-of-the-art regionalization methods, namely, Agglomerative Clustering, SKATER, REDCAP, AZP, and Max-P-Regions using real world social determinant of health (SDOH) data. The scale of real world SDOH data, up to 1 million data points in this study, not only compares the algorithms over different data sets but provides a stress test for each individual regionalization algorithm, most of which have never been run on such scales previously. We use several new geographic metrics to compare algorithms as well as perform a comparative memory analysis. The prevailing regionalization method is then compared with unconstrained K-Means clustering on their ability to separate real health data in Virginia and Washington DC.Barrett Lattimer, Alan Lattimerwork_urcsxl74k5atjpohdgrhdqhbuuFri, 23 Sep 2022 00:00:00 GMTLayered character models for fast physics-based simulation
https://scholar.archive.org/work/e2u77bn53fd65kfxyzs6sycpmq
This thesis presents two different layered character models that are ready to be used in physics-based simulations, in particular they enable convincing character animations in real-time. We start by introducing a two-layered model consisting of rigid bones and an elastic soft tissue layer that is efficiently constructed from a surface mesh of the character and its underlying skeleton. Building on this model, we introduce Fast Projective Skinning, a novel approach for physics-based character skinning. While maintaining real-time performance it overcomes the well-known artifacts of commonly used geometric skinning approaches. It further enables dynamic effects and resolves local and global self-collisions. In particular, our method neither requires skinning weights, which are often expensive to compute or tedious to hand-tune, nor a complex volumetric tessellation, which fails for many real-world input meshes due to self-intersections. By developing a custom-tailored GPU implementation and a high-quality upsampling method, our ap- proach is the first skinning method capable of detecting and handling arbitrary global collisions in real-time. In the second part of the thesis, we extend the idea of a simplified two-layered volumetric model by developing an anatomically plausible three-layered representation of human virtual characters. Starting with an anatomy model of the male and female body, we show how to generate a layered body template for both sexes. It is composed of three surfaces for bones, muscles and skin enclosing the volumetric skeleton, muscles and fat tissues. Utilizing the simple structure of these templates, we show how to fit them to the surface scan of a person in just a few seconds. 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. Additionally, we demonstrate how to efficiently embed fine-scale anatomical details, such as high [...]Martin Komaritzan, Technische Universität Dortmundwork_e2u77bn53fd65kfxyzs6sycpmqThu, 22 Sep 2022 00:00:00 GMT