12,710 research outputs found
Position-Based Multi-Agent Dynamics for Real-Time Crowd Simulation (MiG paper)
Exploiting the efficiency and stability of Position-Based Dynamics (PBD), we
introduce a novel crowd simulation method that runs at interactive rates for
hundreds of thousands of agents. Our method enables the detailed modeling of
per-agent behavior in a Lagrangian formulation. We model short-range and
long-range collision avoidance to simulate both sparse and dense crowds. On the
particles representing agents, we formulate a set of positional constraints
that can be readily integrated into a standard PBD solver. We augment the
tentative particle motions with planning velocities to determine the preferred
velocities of agents, and project the positions onto the constraint manifold to
eliminate colliding configurations. The local short-range interaction is
represented with collision and frictional contact between agents, as in the
discrete simulation of granular materials. We incorporate a cohesion model for
modeling collective behaviors and propose a new constraint for dealing with
potential future collisions. Our new method is suitable for use in interactive
games.Comment: 9 page
A Survey of Ocean Simulation and Rendering Techniques in Computer Graphics
This paper presents a survey of ocean simulation and rendering methods in
computer graphics. To model and animate the ocean's surface, these methods
mainly rely on two main approaches: on the one hand, those which approximate
ocean dynamics with parametric, spectral or hybrid models and use empirical
laws from oceanographic research. We will see that this type of methods
essentially allows the simulation of ocean scenes in the deep water domain,
without breaking waves. On the other hand, physically-based methods use
Navier-Stokes Equations (NSE) to represent breaking waves and more generally
ocean surface near the shore. We also describe ocean rendering methods in
computer graphics, with a special interest in the simulation of phenomena such
as foam and spray, and light's interaction with the ocean surface
Machine Understanding of Human Behavior
A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior
BioSimulator.jl: Stochastic simulation in Julia
Biological systems with intertwined feedback loops pose a challenge to
mathematical modeling efforts. Moreover, rare events, such as mutation and
extinction, complicate system dynamics. Stochastic simulation algorithms are
useful in generating time-evolution trajectories for these systems because they
can adequately capture the influence of random fluctuations and quantify rare
events. We present a simple and flexible package, BioSimulator.jl, for
implementing the Gillespie algorithm, -leaping, and related stochastic
simulation algorithms. The objective of this work is to provide scientists
across domains with fast, user-friendly simulation tools. We used the
high-performance programming language Julia because of its emphasis on
scientific computing. Our software package implements a suite of stochastic
simulation algorithms based on Markov chain theory. We provide the ability to
(a) diagram Petri Nets describing interactions, (b) plot average trajectories
and attached standard deviations of each participating species over time, and
(c) generate frequency distributions of each species at a specified time.
BioSimulator.jl's interface allows users to build models programmatically
within Julia. A model is then passed to the simulate routine to generate
simulation data. The built-in tools allow one to visualize results and compute
summary statistics. Our examples highlight the broad applicability of our
software to systems of varying complexity from ecology, systems biology,
chemistry, and genetics. The user-friendly nature of BioSimulator.jl encourages
the use of stochastic simulation, minimizes tedious programming efforts, and
reduces errors during model specification.Comment: 27 pages, 5 figures, 3 table
Triangulation of uniform particle systems: its application to the implicit surface texturing
Particle systems, as originally presented by Witkin and Heckbert [32], offer an elegant solution to sample implicit
surfaces of arbitrary genus, while providing an extremely regular distribution of samples over the surface. In this
paper, we present an ef cient technique that uses particle systems to rapidly generate a triangular mesh over an
implicit surface, where each triangle is almost equilateral. The major advantage of such a triangulation is that
it minimizes the deformations between the mesh and the underlying implicit surface. We exploit this property
by using few triangular texture samples mapped in a non-periodic fashion as presented by Neyret and Cani [16].
The result is a pattern-based texturing method that maps homogeneous non-periodic textures to arbitrary implicit
surfaces, with almost no deformation
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