Human sensitivity and use of natural image statistics

人类敏感性和自然图像统计的使用

• 批准号: 341032-2011
• 负责人: Johnson, Aaron
• 金额: $ 1.75万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2014
• 资助国家: 加拿大
• 起止时间: 2014-01-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=549269
• 关键词: Human; sensitivity; use; natural; image

Humans live in a visually complex and dynamic environment, yet we are capable of perceiving and processing information from our surroundings, make perceptual judgments, and create a behavioural response in a few short milliseconds. The aim of my research is to better understand how the brain can accomplish this. The environment and daily tasks that humans must perform have shaped the design and functioning of our visual system. Therefore, by studying the visual sources of information within our world, we can investigate the function and design of human vision. My research focuses on scene perception, our ability to rapidly recognize a scene. Specifically, how the visual information within a scene, such as texture and colour, is used in the recognition of natural scenes (photographs of the real world, as opposed to synthetic images). By manipulating the visual properties of scenes (e.g. brightness, colour, texture), I aim to investigate the sensitivity of humans to such manipulations, and discover which features are humans most sensitive to, and which we are least sensitive to. This research will verify if findings from studies using synthetic computer-generated images, which are traditionally used to study vision, can be applied to more complex images such as scenes. I will also investigate if these manipulations within the scene properties can affect daily visual tasks such as search and scene recognition that humans must perform with the visual features. This will allow us to investigate which visual features of an image are important in scene recognition, and when they used. The knowledge obtained by this research will expand our understanding of the human visual system, and help advance our understanding of the human mind, from how we extract the visual information within a scene to how we perform everyday vision tasks. The findings will also be useful for many practical applications, such as detecting image manipulations (forgery) in digital photographs, improving human interface design, improving instrument panel design for cars and aircraft, and helping to locate camouflaged objects in photographs.

人类生活在一个视觉复杂和动态的环境中，但我们能够感知和处理来自周围环境的信息，做出感性判断，并在短短几毫秒内创造出行为反应。我研究的目的是更好地理解大脑是如何做到这一点的。人类必须执行的环境和日常任务塑造了我们视觉系统的设计和功能。因此，通过研究我们世界中的视觉信息来源，我们可以研究人类视觉的功能和设计。我的研究重点是场景感知，即我们快速识别场景的能力。具体地说，场景中的视觉信息，如纹理和颜色，如何用于识别自然场景(真实世界的照片，而不是合成图像)。通过操纵场景的视觉属性(如亮度、颜色、纹理)，我的目标是调查人类对这些操纵的敏感性，并发现人类对哪些特征最敏感，哪些我们最不敏感。这项研究将验证使用传统上用于研究视觉的合成计算机生成图像的研究结果是否可以应用于更复杂的图像，如场景。我还将调查场景属性中的这些操作是否会影响人类必须使用视觉功能执行的日常视觉任务，如搜索和场景识别。这将使我们能够调查图像的哪些视觉特征在场景识别中是重要的，以及它们何时使用。通过这项研究获得的知识将扩大我们对人类视觉系统的理解，并有助于促进我们对人类思维的理解，从我们如何在场景中提取视觉信息到如何执行日常视觉任务。这些发现还将有助于许多实际应用，如检测数字照片中的图像篡改(伪造)、改进人机界面设计、改进汽车和飞机的仪表板设计，以及帮助定位照片中的伪装对象。