A framework for discussing the motion blur image generation process is formulated. Previous work is studied in the context of this framework. Due to the implicit assumptions on low temporal frequencies in most motion blur algorithms, issues involved in large screen space movements and fast illumination changes in time have not been adequately addressed so far. A new approach that does not make these assumptions is introduced to solve the spatial-temporal geometric and shading aliasing problems separately. Based on newly developed adaptive algorithms in the spatial-temporal domain, an implementation of the new approach is developed to efficiently deliver high-quality motion blurred images in general computer graphics production environments.

Maya is the new 3D software package recently released by Alias I Wavefront for creating state of the art character animation and visual effects. Built on a next generation advanced architecture, Maya delivers high speed interaction and high productivity for its users. In the Fall of 1995, the Rendering Team at Alias/Wavefront started from scratch to design and implement a renderer for the Maya project. This was a very challenging task, requiring the efficient generation of high quality images for a next generation 3D application that was still under development. In addition, we were expected to match or exceed the capabilities of our existing popular rendering products (as well as those from our competitors). In January of 1998, the all new renderer was delivered with Maya 1.0. It includes a comprehensive user interface that is well integrated with the rest of the system, and a batch renderer that is capable of efficiently generating a full spectrum of high quality visual effects. Currently, there are high end computer graphics (CG) productions in progress that are using the Maya Renderer. We concentrate on our batch renderer implementation effort. We describe the philosophy, design decisions, and the tasks we set out to achieve in 1995. We then evaluate the delivered system based on images generated with the renderer.

In a distributed ray tracer, the sampling strategy is the crucial part of the direct lighting calculation. Monte Carlo integration with importance sampling is used to carry out this calculation. Importance sampling involves the design of integrand-specific probability density functions that are used to generate sample points for the numerical quadrature. Probability density functions are presented that aid in the direct lighting calculation from luminaires of various simple shapes. A method for defining a probability density function over a set of luminaires is presented that allows the direct lighting calculation to be carried out with a number of sample points that is independent of the number of luminaires.