Grid-based methods have difficulty resolving features on or below the scale of the underlying grid. Although adaptive methods (e.g. RLE, octrees) can alleviate this to some degree, separate techniques are still required for simulating small-scale phenomena such as spray and foam, especially since these more diffuse materials typically behave quite differently than their denser counterparts. In this paper, we propose a two-way coupled simulation framework that uses the particle level set method to efficiently model dense liquid volumes and a smoothed particle hydrodynamics (SPH) method to simulate diffuse regions such as sprays. Our novel SPH method allows us to simulate both dense and diffuse water volumes, fully incorporates the particles that are automatically generated by the particle level set method in under-resolved regions, and allows for two way mixing between dense SPH volumes and grid-based liquid representations.

A long-standing difficulty in the development of introductory courses in computer graphics is balancing the educational necessity of ensuring mastery of fundamental graphical concepts with the highly desirable goal of exciting and inspiring students to further study by enabling them to produce visually interesting programming projects. Recently, we have developed a modified curriculum predicated on the extensive integration of the OpenGL Shading Language with a more traditional pedagogical approach. We utilized this curriculum in the quarter-long, upper-division introductory graphics course taught in the Department of Computer Science at the University of California, Santa Cruz. Our experience indicates that making shading an integral part of the entry-level curriculum inculcates students with a comprehensive understanding of the algorithms and mathematical concepts that underlie modern graphical systems, while simultaneously equipping them with the tools necessary to produce complex projects with state-of-the-art technology.

This paper describes Scavenger Hunt, a team-based orientation activity for incoming freshmen in the Department of Computer Science at the University of Illinois. Like many large research universities, Illinois has struggled with the high attrition rate of first-year students in computing disciplines. Scavenger Hunt, which has been held each of the past three years, is intended to foster a sense of community within the department and acclimate new students to undergraduate life as computer science majors. A unique aspect of the activity is the use of handheld computers to manage most aspects of the competition, which enables physically handicapped students to participate on an equal footing with their able-bodied peers. Thus far, Scavenger Hunt has been directly responsible for the increased participation of new students in departmental activities and organizations. In addition, we have observed a significant correlation between student participation in Scavenger Hunt and retention rates in the department. Along with other retention-oriented activities, Scavenger Hunt is measurably improving the attitude of new students towards computer science.

Point-based representations are becoming increasingly common in computer graphics, especially for visualizing data sets where the number of points is large relative to the number of pixels involved in their display. When dealing with sparse point sets, however, many traditional rendering algorithms for point data perform poorly, either by generating blurry or non-occluding surface representations or by requiring extensive pre-processing to yield good results. In this paper we present a novel method for point-based surface visualization that we call Voronoi rasterization. Voronoi rasterization uses modern programmable graphics hardware to generate occluding surface representations from sparse, oriented point sets without preprocessing. In particular, Voronoi rasterization clips away overlapping flaps between neighboring splats and generates an approximation of the Voronoi diagram of the points under the surface's geodesic distance.

We utilize a high-dimensional parametric design space to support a novel and intuitive method for 3D modeling. Users visually explore the design space and pick models using a continuous, map-like interface. We leverage models created by the user community to learn underlying structure in the space via kernel density estimation. This mapping of the space is maintained by a server that synchronizes all the deployed design tools. The tools leverage the mapping to allow users with no prior modeling experience to easily create unique designs by interpolating between and extrapolating from landmark models. The result is a self-reinforcing design system that becomes easier to use as more people participate. Our prototype tree modeling tool was downloaded by over six thousand users from more than eighty countries in the month following its release. Over fifteen hundred trees were voluntarily picked from the roughly hundred dimensional tree space. We report on usage patterns gathered through this deployment and on subsequent user surveys.

The problem of approximating a given input mesh with a less complex but geometrically faithful representation is well-established in computer graphics. Given the visual complexity required to create realistic-looking scenes, simplification efforts can be essential to efficient rendering. Level-of-detail representations figure prominently in real-time applications such as virtual reality, terrain modeling, and scientific visualization, and as a result there is significant demand for effective algorithms for mesh simplification. In this paper, I give a basic overview of the components of some of the most common mesh simplification algorithms and evaluate their strengths and deficiencies.

In recent years, the problems associated with multimedia indexing and retrieval have grown increasingly prevalent. As a result, the need for systems that allow for the quick and easy retrieval of specific audiovisual content is pronounced. Central to most such systems is the ability to compare two files to determine the degree to which they are similar. In this thesis, we propose simple methods for determining the degree of similarity of multimedia files based on a metrical analysis of their audio and video data and demonstrate that most of these methods can be quite successful. In particular, we define two files to be similar if they are part of the same series and produced by the same source. We also propose a general mathematical model for incorporating these metrics into a formal definition of similarity, which can be trained to increase accuracy based on user feedback.

Dryad lets you intuitively create beautiful trees for your virtual world or game. In Dryad, you create a tree by visually navigating to it through a design space: the space of all trees. This space has close to a hundred dimensions and Dryad lets you move around it as if it were a city map. To help you find your way, Dryads around the world communicate to share which trees were picked in the past. A collaborative mapping of the tree space emerges, which your Dryad uses to gently steer you towards high-quality finds. We call this collaborative design space exploration.