This paper introduces particle systems--a method for modeling fuzzy objects such as fire, clouds, and water. Particle systems model an object as a cloud of primitive particles that define its volume. Over a period of time, particles are generated into the system, move and change form within the system, and die from the system. The resulting model is able to represent motion, changes of form, and dynamics that are not possible with classical surface-based representations. The particles can easily be motion blurred, and therefore do not exhibit temporal aliasing or strobing. Stochastic processes are used to generate and control the many particles within a particle system. The application of particle systems to the wall of fire element from the Genesis Demo sequence of the film Star Trek II: The Wrath of Khan [10] is presented.

We present a solution to the aliasing problem for shadow algorithms that use depth maps. The solution is based on a new filtering technique called percentage closer filtering. In addition to antialiasing, the improved algorithm provides soft shadow boundaries that resemble penumbrae. We describe the new algorithm in detail, demonstrate the effects of its parameters, and analyze its performance.

We present a solution to the aliasing problem for shadow algorithms that use depth maps. The solution is based on a new filtering technique called percentage closer filtering. In addition to antialiasing, the improved algorithm provides soft shadow boundaries that resemble penumbrae. We describe the new algorithm in detail, demonstrate the effects of its parameters, and analyze its performance.

Detail enhances the visual richness and realism of computergenerated images. Our stochastic modelling approach, called particle systems, builds complex pictures from sets of simple, volume-filling primitives. For example, structured particle systems have been used to generate trees and a grass-covered forest floor. Particle systems can produce so much irregular, three-dimensional detail that exact shading and visible surface calculations become infeasible. We describe approximate and probabilistic algorithms for shading and the visible surface problem. Because particle systems algorithms generate richlydetailed images, it is hard to detect any deviation from an exact rendering. Recent work in stochastic modelling also enables us to model complex motions with random variation, such as a field of grass blowing in the breeze. We analyze the performance of our current algorithms to understand the costs of our stochastic modelling approach.

This paper introduces particle systems--a method for modeling fuzzy objects such as fire, clouds, and water. Particle systems model an object as a cloud of primitive particles that define its volume. Over a period of time, particles are generated into the system, move and change form within the system, and die from the system. The resulting model is able to represent motion, changes of form, and dynamics that are not possible with classical surface-based representations. The particles can easily be motion blurred, and therefore do not exhibit temporal aliasing or strobing. Stochastic processes are used to generate and control the many particles within a particle system. The application of particle systems to the wall of fire element from the Genesis Demo sequence of the film Star Trek II: The Wrath of Khan [10] is presented.