Stochastic microgeometry for displacement mapping

Proceedings of Shape Modeling International 2005, June 2005, pp. 164-173. Retrieved 3/16/2006 from http://www.cs.drexel.edu/~david/Papers/schroeder_SMI05.pdf.Creating surfaces with intricate small-scale features (microgeometry) and detail is an important task in geometric modeling and computer graphics. We present a model processing method capable of producing a wide variety of complex surface features based on displacement mapping and stochastic geometry. The latter is a branch of mathematics that analyzes and characterizes the statistical properties of spatial structures. The technique has been incorporated into an interactive modeling environment that supports the design of stochastic microgeometries. Additionally a tool has been developed that provides random exploration of the technique's entire parameter space by generating sample microgeometry over a broad range of values. We demonstrate the effectiveness of our technique by creating diverse, complex surface structures for a variety of geometric models, e.g. arrowheads, candy bars, busts, planets and coral

Fourth-order flows in surface modelling

This short article is a brief account of the usage of fourth-order curvature flow in surface modelling

A digital definition method for manufacturing model of aircraft integral panel

The manufacturing model of aircraft integral panel is presented based on the analysis of its structure and manufacturing process. The manufacturing model for each key process consists of model for processing and model for workpiece to bridge digital design and fabricating. Model for workpiece is used to express the target part information at the end of some operation. Model for processing is used to describe the intermediate state information, and it aims to attain but is different the workpiece because of process factors. The definition flow of the manufacturing model is given. The modeling approach of integral panel part blank from shot peen forming part model orienting to NC cutting is proposed and exemplified. It is analyzed that the approaches above can define the models accurately and totally to meet the needs of process planning , NC fabricating and inspecting

Data-Driven Shape Analysis and Processing

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis, through reviewing the literature and relating the existing works with both qualitative and numerical comparisons. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.Comment: 10 pages, 19 figure