Showing papers by "Michael Garland published in 2002"

Towards real-time texture synthesis with the jump map

Abstract: While texture synthesis has been well-studied in recent years, real-time techniques remain elusive. To help facilitate real-time texture synthesis, we divide the task of texture synthesis into two phases: a relatively slow analysis phase, and a real-time synthesis phase. Any particular texture need only be analyzed once, and then an unlimited amount of texture may be synthesized in real-time. Our analysis phase generates a jump map, which stores for each input pixel a set of matching input pixels (jumps). Texture synthesis proceeds in real-time as a random walk through the jump map. Each new pixel is synthesized by extending the patch of input texture from which one of its neighbours was copied. Occasionally, a jump is taken through the jump map to begin a new patch. Despite the method's extreme simplicity, its speed and output quality compares favourably with recent patch-based algorithms.

A multiphase approach to efficient surface simplification

Abstract: We present a new multiphase method for efficiently simplifying polygonal surface models of arbitrary size. It operates by combining an initial out-of-core uniform clustering phase with a subsequent in-core iterative edge contraction phase. These two phases are both driven by quadric error metrics, and quadrics are used to pass information about the original surface between phases. The result is a method that produces approximations of a quality comparable to quadric-based iterative edge contraction, but at a fraction of the cost in terms of running time and memory consumption.

Permission grids: practical, error-bounded simplification

Abstract: We introduce the permission grid, a spatial occupancy grid which can be used to guide almost any standard polygonal surface simplification algorithm into generating an approximation with a guaranteed geometric error bound. In particular, all points on the approximation are guaranteed to be within some user-specified distance from the original surface. Such bounds are notably absent from many current simplification methods, and are becoming increasingly important for applications in scientific computing and adaptive level of detail control. Conceptually simple, the permission grid defines a volume in which the approximation must lie, and does not permit the underlying simplification algorithm to generate approximations outside the volume.The permission grid makes three important, practical improvements over current error-bounded simplification methods. First, it works on arbitrary triangular models, handling all manners of mesh degeneracies gracefully. Further, the error tolerance may be easily expanded as simplification proceeds, allowing the construction of an error-bounded level of detail hierarchy with vertex correspondences among all levels of detail. And finally, the permission grid has a representation complexity independent of the size of the input model, and a small running time overhead, making it more practical and efficient than current methods with similar guarantees.