Problems for a Theory of Lightness Anchoring

亮度锚定理论的问题

• 批准号: 9906747
• 负责人: Alan Gilchrist
• 金额: $ 28万
• 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: 1999
• 资助国家: 美国
• 起止时间: 1999-09-01 至 2003-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9906747&HistoricalAwards=false
• 关键词: Problems; Theory; Lightness; Anchoring

The goal of the proposed project is to determine how the human visual system computes the black, gray and white values of object surfaces represented in the optical image projected onto the retina. This problem has not yet been solved for machine vision. For example, there is currently no program that can determine the surface colors of objects within a video image. A key part of the problem lies in disentangling variations in image intensity that are due to light and shadow from those that are due to light and dark gray surfaces. The work proceeds using the method of psychophysics. Visual images or displays are created that, when viewed under controlled conditions, allow a test between competing theories or hypotheses. Ideally, for example, an image might be created so that a given target surface within the image should appear white according to Theory A but black according to Theory B. The image is then viewed by human observers, who report the appearance of the target surface. Three years ago, the PI proposed a new theory based on the concept of anchoring. According to this theory, a complex image is parsed by the visual system into frameworks, or perceptual groups, based on rules of grouping. For any given surface, several lightness (gray scale) values are computed, one for each group to which it belongs. The shade of gray actually perceived for that surface is a weighted value of each of these computed values. The work proposed here will extend the theory into a class of illusions that involve spatial intensity gradients. The work will also focus on certain experience effects: how the perceived gray value is influenced by prior exposure to related scenes. Finally, a series of experiments will examine how the relative area of surfaces influences their perceived gray level, especially in more complex images. The project will also include the creation of a web page containing a comprehensive collection of visual illusions in lightness. This publicly accessible collection is likely to be well used by educators and other researchers.

该项目的目标是确定人类视觉系统如何计算投射到视网膜上的光学图像中所表示的物体表面的黑色、灰色和白色值。 这个问题在机器视觉中还没有得到解决。 例如，目前没有程序可以确定视频图像中对象的表面颜色。 这个问题的关键部分在于将由于光和阴影引起的图像强度变化与由于亮和深灰色表面引起的图像强度变化分开。 这项工作使用心理物理学的方法进行。 视觉图像或显示被创建，当在受控条件下观看时，允许在竞争理论或假设之间进行测试。 理想地，例如，可以创建图像，使得图像内的给定目标表面根据理论A应该呈现白色，但是根据理论B应该呈现黑色。 然后由人类观察者观察图像，并报告目标表面的外观。三年前，PI提出了一个基于锚定概念的新理论。 根据这一理论，一个复杂的图像被视觉系统解析成框架，或感知组，基于分组规则。 对于任何给定的表面，计算几个亮度（灰度）值，一个对应于它所属的每个组。 该表面实际感知到的灰色阴影是这些计算值中的每一个的加权值。 这里提出的工作将扩展理论到一类错觉，涉及空间强度梯度。 这项工作还将集中在某些经验的影响：如何感知灰度值是受先前暴露于相关场景。 最后，一系列的实验将研究表面的相对面积如何影响它们的感知灰度，特别是在更复杂的图像中。 该项目还将包括创建一个网页，其中包含一个全面收集的视觉错觉的亮度。 这一可公开访问的集合可能会被教育工作者和其他研究人员很好地使用。