Surface color perception and illuminant cues in dynamic three-dimensional scenes

动态三维场景中的表面颜色感知和光源线索

• 批准号: 1059166
• 负责人: Laurence Maloney
• 金额: $ 32.41万
• 依托单位: New York University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-04-01 至 2014-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1059166&HistoricalAwards=false
• 关键词: Surface; color; perception; illuminant; cues

One of the most impressive aspects of human vision is the stability of surface colors under very different lighting conditions. The visual system is remarkably good at separating the color of the illumination from the actual colors of surfaces and engineers are not currently able to build a camera that can match human performance. Most previous research has focused on very simple stimuli consisting of a small number of flat colored surfaces arranged on a flat panel under diffuse (uniform) lighting. The proposed research makes use of recent advances in computer graphics to create physically-accurate virtual scenes filled with objects at many different depths and orientations illuminated by realistic daylight illuminants mimicking the effects of sun, sky and cloud cover. The major challenge for the visual system in such scenes is that illumination is rarely uniform. In the research proposed here, the investigator will analyze how the visual system uses simple "cues" about illumination conditions such as surface shading and highlights to estimate stable surface colors. The use of eye tracking technology allows the experimenter to monitor where the observer looks in gathering information about the conditions of scene illumination. The proposed research represents the first use of eye-tracking technology to study surface color perception.The human ability to assign stable surface colors and stable shapes to objects is an extraordinary achievement. This research will lead to a better understanding of how the brain adaptively makes use of sources of information about depth and color in scenes which, in turn, will provide a better understanding of how the brain reacts to injury, disease and even normal aging. Moreover, research on how the brain uses cues to scene layout and lighting can inform the production of artificial visual systems that duplicate biological function. Subtle changes in surface color accompany many disease states in plant and animal and such systems would have evident applications in remote sensing, from monitoring crops to early detection of illness.

人类视觉最令人印象深刻的方面之一是在非常不同的照明条件下表面颜色的稳定性。视觉系统非常善于将照明的颜色与表面的实际颜色分离开来，工程师目前还无法制造出能够与人类表现相匹配的相机。大多数以前的研究都集中在非常简单的刺激，包括少量的平面彩色表面排列在一个平面上的漫射（均匀）照明。拟议的研究利用计算机图形学的最新进展来创建物理上精确的虚拟场景，其中充满了由逼真的日光光源照亮的许多不同深度和方向的对象，模仿太阳，天空和云层的效果。在这样的场景中，视觉系统的主要挑战是照明很少是均匀的。在这里提出的研究中，研究人员将分析视觉系统如何使用关于照明条件的简单“线索”，如表面阴影和高光来估计稳定的表面颜色。眼动追踪技术的使用允许实验者监视观察者在收集有关场景照明条件的信息时所看的地方。这项研究是首次使用眼动追踪技术来研究物体表面的颜色感知。人类能够为物体赋予稳定的表面颜色和形状，这是一项非凡的成就。这项研究将有助于更好地了解大脑如何自适应地利用场景中有关深度和颜色的信息源，从而更好地了解大脑如何对损伤，疾病甚至正常衰老做出反应。此外，关于大脑如何使用场景布局和照明的线索的研究可以为复制生物功能的人工视觉系统的产生提供信息。表面颜色的微妙变化伴随着植物和动物的许多疾病状态，这种系统将在遥感中有明显的应用，从监测作物到疾病的早期检测。