Mechanisms for the Perception of Surface Qualities

表面质量的感知机制

• 批准号: 0345805
• 负责人: Edward Adelson
• 金额: --
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-08-01 至 2008-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0345805&HistoricalAwards=false
• 关键词: Mechanisms; Perception; Surface; Qualities

Even the best computer vision system falls far short of human vision. A person has no problem recognizing metal as metal or wood as wood. These are examples of material perception in which vision relies on combinations of color, texture, transparency, and glossiness to recognize the material surface of objects. With NSF Support Dr. Edward Adelson studies how perception puts information together, thereby allowing material perception. His working hypothesis is that human vision relies on certain statistical relationships between colors and patterns within an image, and uses these to infer the material. However, the exact nature of these relationships remains to be understood.Broader impacts of the research are important in everyday life. People care greatly about the appearance of their skin and hair, the clothing they wear, and the food they eat. If we can understand the principles that determine material perception, it will help industrial researchers who seek to make new products with improved surface appearance, such as new kinds of cosmetics or paint. An understanding of material perception may also pay off in better machine vision systems. For instance, an automated vehicle should be able to distinguish pavement, dirt, mud, or ice and adjust its driving accordingly, but today's machine vision systems find such problems quite difficult. By emulating the mechanisms of human vision, we can develop more powerful machine vision systems.

即使是最好的计算机视觉系统也远远远远远远没有人类视野。 一个人识别金属或木材的金属毫无问题。 这些是物质感知的例子，其中视觉依赖于识别物体的材料表面的颜色，纹理，透明度和光泽度的组合。 NSF支持爱德华·阿德尔森（Edward Adelson）博士研究感知如何将信息汇总在一起，从而允许物质感知。 他的工作假设是，人类的视野依赖于图像中颜色和模式之间的某些统计关系，并使用这些关系来推断材料。 但是，这些关系的确切性质还有待理解。研究对日常生活的影响很重要。 人们非常关心皮肤和头发的外观，穿着的衣服以及所吃的食物。 如果我们能够理解确定物质感知的原则，它将帮助试图制造具有改善表面外观的新产品的工业研究人员，例如新型的化妆品或油漆。 对材料感知的理解也可以在更好的机器视觉系统中获得回报。 例如，自动化的车辆应该能够区分人行道，污垢，泥浆或冰，并相应地调整其驾驶，但是当今的机器视觉系统发现此类问题非常困难。 通过模拟人类视觉的机制，我们可以开发更强大的机器视觉系统。