Automatic simplification of particle system dynamics

O'Brien, David; Fisher, Seymour

doi:10.1109/ca.2001.982395

Cited by 26 publications

(18 citation statements)

References 16 publications

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“…For faster rendering, geometry can be simplified and displayed at multiple Levels of Detail (LOD) in order to attain a target frame-rate and perceptual heuristics can be used to make this as imperceptible as possible [Funkhouser and Séquin 1993;Luebke and Hallen 2001]. Similarly, simpler physical models, called Simulation Levels of Detail (SLOD) [Carlson and Hodgins 1997;Chenney and Forsyth 1997;O'Brien et al 2001;Brogan and Hodgins 2002] or simulation proxies [Chenney et al 2001] can be used to reduce simulation times by applying simpler dynamics computations.…”

Section: Unavoidable Distortionsmentioning

confidence: 99%

Evaluating the visual fidelity of physically based animations

O’Sullivan

Dingliana

Giang

et al. 2003

ACM SIGGRAPH 2003 Papers

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For many systems that produce physically based animations, plausibility rather than accuracy is acceptable. We consider the problem of evaluating the visual quality of animations in which physical parameters have been distorted or degraded, either unavoidably due to real-time frame-rate requirements, or intentionally for aesthetic reasons. To date, no generic means of evaluating or predicting the fidelity, either physical or visual, of the dynamic events occurring in an animation exists. As a first step towards providing such a metric, we present a set of psychophysical experiments that established some thresholds for human sensitivity to dynamic anomalies, including angular, momentum and spatio-temporal distortions applied to simple animations depicting the elastic collision of two rigid objects. In addition to finding significant acceptance thresholds for these distortions under varying conditions, we identified some interesting biases that indicate non-symmetric responses to these distortions (e.g., expansion of the angle between postcollision trajectories was preferred to contraction and increases in velocity were preferred to decreases). Based on these results, we derived a set of probability functions that can be used to evaluate the visual fidelity of a physically based simulation. To illustrate how our results could be used, two simple case studies of simulation levels of detail and constrained dynamics are presented.

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Section: Unavoidable Distortionsmentioning

confidence: 99%

Evaluating the visual fidelity of physically based animations

O’Sullivan

Dingliana

Giang

et al. 2003

ACM SIGGRAPH 2003 Papers

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“…In addition to diffuse phenomena such as fire, smoke, and explosions, particle systems can also model concrete objects such as dense trees in a forest [12], folded cloth and fabric [13], [14], and simulated fluid motion [15], [16]. Realistic particle movement is often achieved by simulating real-world physics [17].…”

Section: A Particle Systemsmentioning

confidence: 99%

“…There are several ways to optimize particle system rendering including level of detail (LOD) [15], batch rendering [49], and GPU acceleration [50]. NEAT Particles is compatible with all such methods; however they are not explored in this implementation.…”

Section: E Renderingmentioning

confidence: 99%

Interactive Evolution of Particle Systems for Computer Graphics and Animation

Hastings

Guha

Stanley

2009

IEEE Trans. Evol. Computat.

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Abstract-Interactive Evolutionary Computation (IEC) creates the intriguing possibility that a large variety of useful content can be produced quickly and easily for practical computer graphics and gaming applications. To show that IEC can produce such content, this paper applies IEC to particle system effects, which are the de facto method in computer graphics for generating fire, smoke, explosions, electricity, water, and many other special effects. While particle systems are capable of producing a broad array of effects, they require substantial mathematical and programming knowledge to produce. Therefore, efficient particle system generation tools are required for content developers to produce special effects in a timely manner. This paper details the design, representation, and animation of particle systems via two IEC tools called NEAT Particles and NEAT Projectiles. Both tools evolve artificial neural networks (ANN) with the NeuroEvolution of Augmenting Topologies (NEAT) method to control the behavior of particles. NEAT Particles evolves general-purpose particle effects, whereas NEAT Projectiles specializes in evolving particle weapon effects for video games. The primary advantage of this NEAT-based IEC approach is to decouple the creation of new effects from mathematics and programming, enabling content developers without programming knowledge to produce complex effects. Furthermore, it allows content designers to produce a broader range of effects than typical development tools. Finally, it acts as a concept generator, allowing content creators to interactively and efficiently explore the space of possible effects. Both NEAT Particles and NEAT Projectiles demonstrate how IEC can evolve useful content for graphical media and games, and are together a step toward the larger goal of automated content generation.

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“…Their approach required the user to manually design the simplified models for each level of detail. Subsequent work has sought to generate approximated models automatically, for example for particle systems [18], plants [19], and hair [20]. Chenney and Forsyth [21] took a different approach, culling out-of-view objects by not solving their equations of motion, and using knowledge of the statistics of the motion to predict their plausible states when they reenter the view.…”

Section: Related Workmentioning

confidence: 99%