5,710 research outputs found
Real-time simulation and visualisation of cloth using edge-based adaptive meshes
Real-time rendering and the animation of realistic virtual environments and characters
has progressed at a great pace, following advances in computer graphics hardware
in the last decade. The role of cloth simulation is becoming ever more important in
the quest to improve the realism of virtual environments.
The real-time simulation of cloth and clothing is important for many applications
such as virtual reality, crowd simulation, games and software for online clothes shopping.
A large number of polygons are necessary to depict the highly
exible nature of
cloth with wrinkling and frequent changes in its curvature. In combination with the
physical calculations which model the deformations, the effort required to simulate
cloth in detail is very computationally expensive resulting in much diffculty for its
realistic simulation at interactive frame rates. Real-time cloth simulations can lack
quality and realism compared to their offline counterparts, since coarse meshes must
often be employed for performance reasons.
The focus of this thesis is to develop techniques to allow the real-time simulation of
realistic cloth and clothing. Adaptive meshes have previously been developed to act as
a bridge between low and high polygon meshes, aiming to adaptively exploit variations
in the shape of the cloth. The mesh complexity is dynamically increased or refined to
balance quality against computational cost during a simulation. A limitation of many
approaches is they do not often consider the decimation or coarsening of previously
refined areas, or otherwise are not fast enough for real-time applications.
A novel edge-based adaptive mesh is developed for the fast incremental refinement
and coarsening of a triangular mesh. A mass-spring network is integrated into
the mesh permitting the real-time adaptive simulation of cloth, and techniques are
developed for the simulation of clothing on an animated character
A survey of real-time crowd rendering
In this survey we review, classify and compare existing approaches for real-time crowd rendering. We first overview character animation techniques, as they are highly tied to crowd rendering performance, and then we analyze the state of the art in crowd rendering. We discuss different representations for level-of-detail (LoD) rendering of animated characters, including polygon-based, point-based, and image-based techniques, and review different criteria for runtime LoD selection. Besides LoD approaches, we review classic acceleration schemes, such as frustum culling and occlusion culling, and describe how they can be adapted to handle crowds of animated characters. We also discuss specific acceleration techniques for crowd rendering, such as primitive pseudo-instancing, palette skinning, and dynamic key-pose caching, which benefit from current graphics hardware. We also address other factors affecting performance and realism of crowds such as lighting, shadowing, clothing and variability. Finally we provide an exhaustive comparison of the most relevant approaches in the field.Peer ReviewedPostprint (author's final draft
Virtual Reality Games for Motor Rehabilitation
This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion
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View-dependent adaptive cloth simulation
This paper describes a method for view-dependent cloth simulation using dynamically adaptive mesh refinement and coarsening. Given a prescribed camera motion, the method adjusts the criteria controlling refinement to account for visibility and apparent size in the camera's view. Objectionable dynamic artifacts are avoided by anticipative refinement and smoothed coarsening. This approach preserves the appearance of detailed cloth throughout the animation while avoiding the wasted effort of simulating details that would not be discernible to the viewer. The computational savings realized by this method increase as scene complexity grows, producing a 2× speed-up for a single character and more than 4× for a small group
Learning to Navigate Cloth using Haptics
We present a controller that allows an arm-like manipulator to navigate
deformable cloth garments in simulation through the use of haptic information.
The main challenge of such a controller is to avoid getting tangled in, tearing
or punching through the deforming cloth. Our controller aggregates force
information from a number of haptic-sensing spheres all along the manipulator
for guidance. Based on haptic forces, each individual sphere updates its target
location, and the conflicts that arise between this set of desired positions is
resolved by solving an inverse kinematic problem with constraints.
Reinforcement learning is used to train the controller for a single
haptic-sensing sphere, where a training run is terminated (and thus penalized)
when large forces are detected due to contact between the sphere and a
simplified model of the cloth. In simulation, we demonstrate successful
navigation of a robotic arm through a variety of garments, including an
isolated sleeve, a jacket, a shirt, and shorts. Our controller out-performs two
baseline controllers: one without haptics and another that was trained based on
large forces between the sphere and cloth, but without early termination.Comment: Supplementary video available at https://youtu.be/iHqwZPKVd4A.
Related publications http://www.cc.gatech.edu/~karenliu/Robotic_dressing.htm
High Performance Algorithms for Counting Collisions and Pairwise Interactions
The problem of counting collisions or interactions is common in areas as
computer graphics and scientific simulations. Since it is a major bottleneck in
applications of these areas, a lot of research has been carried out on such
subject, mainly focused on techniques that allow calculations to be performed
within pruned sets of objects. This paper focuses on how interaction
calculation (such as collisions) within these sets can be done more efficiently
than existing approaches. Two algorithms are proposed: a sequential algorithm
that has linear complexity at the cost of high memory usage; and a parallel
algorithm, mathematically proved to be correct, that manages to use GPU
resources more efficiently than existing approaches. The proposed and existing
algorithms were implemented, and experiments show a speedup of 21.7 for the
sequential algorithm (on small problem size), and 1.12 for the parallel
proposal (large problem size). By improving interaction calculation, this work
contributes to research areas that promote interconnection in the modern world,
such as computer graphics and robotics.Comment: Accepted in ICCS 2019 and published in Springer's LNCS series.
Supplementary content at https://mjsaldanha.com/articles/1-hpc-ssp
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