Evaluating Non-Photorealistic Rendering

评估非真实感渲染

• 批准号: 0227337
• 负责人: Douglas DeCarlo
• 金额: $ 7.31万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-01 至 2003-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0227337&HistoricalAwards=false
• 关键词: Evaluating; Non; Photorealistic; Rendering

ABSTRACT0227337Douglas M. DeCarloRutgers U, New BrunswickWe propose to show that non-photorealistic renderings which exhibit meaningful abstractionare easily understood. Abstract images are designed to make meaningful structure clear. We haveworked on the interactive transformation of photographs into versions which manifest meaningfulabstraction by drawing on eye movement data [DeCarlo & Santella SIGGRAPH 2002, Santella &DeCarlo NPAR 2002]. Over the next year, we intend to carry out psychophysical experiments thatcould both validate our interactive technique, and provide new ways of learning more about humanvision eye movements, in particular.This is high-risk research. Non-photorealistic rendering (NPR) is an established field, but hasnever been evaluated. Psychophysical methods are typically applied to simple patterns (i.e. dotsand blobs). However, our method already involves a close link between NPR and perception andpsychophysics, and our lab maintains close connections with psychophysicists including EileenKowler and Thomas Papathomas (both are, like us, affiliated with the Rutgers Center for CognitiveScience). Many simple conjectures and experiments can be stated naturally in our framework; webelieve we can obtain compelling results.

摘要0227337道格拉斯M. DeCarloRutgers U，新不伦瑞克我们建议表明，表现出有意义的抽象的非真实感渲染很容易理解。抽象图像的目的是使有意义的结构清晰。我们致力于通过利用眼动数据将照片交互转换为有意义的抽象版本[DeCarlo Santella SIGGRAPH 2002，Santella DeCarlo NPAR 2002]。在接下来的一年里，我们打算进行心理物理实验，既可以验证我们的交互技术，又可以提供新的方法来了解更多关于人类视觉的眼球运动，特别是这是一项高风险的研究。非真实感绘制（NPR）是一个成熟的领域，但从来没有被评估。心理物理学方法通常应用于简单的模式（即点和斑点）。然而，我们的方法已经涉及到NPR与感知和心理物理学之间的密切联系，我们的实验室与包括EileenKowler和托马斯帕帕托马斯在内的心理物理学家保持着密切的联系（他们都和我们一样，隶属于罗格斯认知科学中心）。在我们的框架中，可以自然地陈述许多简单的结构和实验;我们相信我们可以获得令人信服的结果。