Human Perception of Depth and Surface Lightness

人类对深度和表面亮度的感知

• 批准号: 0643827
• 负责人: Alan Gilchrist
• 金额: $ 33万
• 依托单位: Rutgers University New Brunswick
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-07-01 至 2011-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0643827&HistoricalAwards=false
• 关键词: Human; Perception; Depth; Surface; Lightness

Though it might surprise the average person, human vision has not yet been explained scientifically. For example, we do not yet have enough information about vision to design a robot that can actually see. No robot or computer exists that can determine the size or even the color of an object in its field of view. Although the perception of size and color is easy for human vision, we do not know what kind of "software" the brain uses to do this. The open questions addressed in this project include how the human visual system detects lightness: the black, white, or gray shade of objects in the visual field, and especially how this detection depends on the perceived distance of that surface. A second issue in this research is methodological: Researchers testing lightness perception using paper of varying lightness have found different results from those found by researchers using computer monitors. Obviously, a theory of visual phenomena would not expect such differences.With support of the National Science Foundation, Dr. Alan Gilchrist will examine the nature of the software of lightness perception. In a series of experiments, Dr. Gilchrist will explore the relations between surface lightness, lightness context, illumination, and surface distance. All the experiments will be conducted in two ways: (1) using actual 3D displays made from paper, and (2) using simulated displays created with CRT images in a mirror stereoscope. This work will clarify a series of nagging and controversial questions concerning the nature of the relationship between lightness perception and depth perception (two of the most important visual dimensions) and between lightness perception and perception of the illumination level. The resulting understanding will have a number of impacts. It will help guide neuroscientists in what to look for in the brain, both in the study of vision itself, and in the study of cognitive processes more generally. The work also will benefit machine vision, by laying the groundwork for successful machine-vision algorithms, thereby enhancing our technical capabilities. The project will also provide a needed service to the field of vision by advancing the integration of two bodies of research on lightness, those using traditional paper and light displays, and those using stereo CRT images.

尽管这可能会让普通人感到惊讶，但人类视觉尚未得到科学解释。例如，我们还没有足够的关于视觉的信息来设计一个能够真正看到东西的机器人。没有机器人或计算机可以确定其视野中物体的大小甚至颜色。虽然尺寸和颜色的感知对于人类视觉来说很容易，但我们不知道大脑使用什么样的“软件”来做到这一点。该项目中解决的开放性问题包括人类视觉系统如何检测亮度：视野中物体的黑色、白色或灰色阴影，特别是这种检测如何取决于该表面的感知距离。这项研究的第二个问题是方法论问题：研究人员使用不同亮度的纸张测试亮度感知，发现结果与研究人员使用计算机显示器得出的结果不同。 显然，视觉现象理论不会预料到这种差异。在国家科学基金会的支持下，艾伦·吉尔克里斯特博士将研究亮度感知软件的本质。在一系列实验中，吉尔克里斯特博士将探索表面亮度、亮度背景、照明和表面距离之间的关系。所有实验都将以两种方式进行：(1) 使用由纸制成的实际 3D 显示器，以及 (2) 使用镜面立体镜中用 CRT 图像创建的模拟显示器。这项工作将澄清一系列令人烦恼和有争议的问题，涉及亮度感知和深度感知（两个最重要的视觉维度）之间以及亮度感知和照明水平感知之间关系的性质。由此产生的理解将产生许多影响。它将有助于指导神经科学家在大脑中寻找什么，无论是在视觉本身的研究中，还是在更广泛的认知过程的研究中。这项工作还将有利于机器视觉，为成功的机器视觉算法奠定基础，从而增强我们的技术能力。该项目还将通过推进两个关于亮度的研究机构（使用传统纸张和光显示器的研究机构以及使用立体 CRT 图像的研究机构）的整合，为视觉领域提供所需的服务。