NSF Young Investigator: Studies in Image Synthesis

NSF 青年研究员：图像合成研究

• 批准号: 9357790
• 负责人: David Salesin
• 金额: $ 31.25万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-08-01 至 1997-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9357790&HistoricalAwards=false
• 关键词: NSF; Young; Investigator; Studies; Image

Photorealistic image synthesis is an important problem for such diverse fields as architecture, lighting and industrial design, remote sensing from satellites and robots, scientific visualization, simulation systems, and entertainment and advertising. It also requires enormous computation. Carefully chosen approximations are therefore essential for making the computation efficient. Unfortunately, few such approximations admit good error metrics, which makes controlling image fidelity difficult at best. In many applications this accuracy is vital. This research develops a controlled-precision rendering approach for general systems of light transport both to provide reliable bounds on accuracy, and also to allow an algorithm to concentrate its effort where the error reduction is largest. In addition to photorealistic image synthesis, research begins in non-photorealistic rendering, an area with great commercial potential that has received relatively little attention to date. Mechanisms are developed to support the generation of effective illustrations from three-dimensional continuous-tone images. Specific research goals include creating a taxonomy of traditional illustration techniques; developing new modeling paradigms, imaging models, and user-interaction methods for specifying and computing illustrations; establishing methods for simplifying geometric models from models with a higher level of detail; and developing techniques for simulating traditional artist tools, such as pencil, chalk, air brush, and watercolor.

真实感图像合成是建筑、照明和工业设计、卫星和机器人遥感、科学可视化、仿真系统以及娱乐和广告等不同领域的重要问题。 它还需要大量的计算。 因此，仔细选择的近似值对于提高计算效率至关重要。 不幸的是，很少有这样的近似承认良好的误差度量，这使得控制图像保真度困难。 在许多应用中，这种精度至关重要。 本研究开发了一种控制精度渲染方法，用于一般的光传输系统，既提供可靠的精度范围，又允许算法将其精力集中在误差减少最大的地方。 除了真实感图像合成之外，研究开始于非真实感渲染，这是一个具有巨大商业潜力的领域，迄今为止受到的关注相对较少。 机制的开发，以支持从三维连续色调图像的有效插图的生成。 具体的研究目标包括创建一个分类的传统插图技术;开发新的建模范式，成像模型，和用户交互方法，用于指定和计算插图;建立简化几何模型的方法，从模型具有更高的细节水平;和开发技术，用于模拟传统的艺术家工具，如铅笔，粉笔，喷枪和水彩。