Attentional Guidance in Real-World Scenes: The Role of Meaning

真实世界的场景包含了大量的、嗡嗡作响的混乱信息。然而，在任何特定的时刻，我们只能感知和理解这些信息的一小部分。我们所看到和理解的是由我们所看的地方决定的。但是，是什么决定了我们的目光呢？这个项目试图回答这个重要的问题。该项目探讨了这样一种观点，即场景的意义在引导我们的眼睛方面起着关键作用。如果我们的假设是正确的，那么我们应该发现，意义预测了人们的目光。这样的结果将推进我们的大脑和思想如何工作的科学知识。研究结果也将有助于计算机科学和工程的应用领域，有助于提高美国的经济竞争力。高科技应用包括虚拟和增强现实、人工视觉和基于凝视的输入系统、行李筛查、医学图像评估、卫星图像分析和其他基于计算机的视觉系统。该项目还将有助于在这些高科技和科学领域培训具有文化和性别多样性的学生和研究人员，促进发展具有全球竞争力的多元化劳动力。在场景观看期间的注意力引导利用场景的视觉属性和其语义内容。虽然视觉特性的作用（例如，物理显著性）对注意引导的影响已经得到了广泛的研究，但对场景的语义内容如何引导注意知之甚少。我的实验室最近的工作表明，当语义内容可用于引导注意力时，物理显着性的影响会减少甚至消除。这些发现开启了重要的新问题，即意义如何以及何时在场景中引导注意力。当前工作背后的中心思想是通过一系列有针对性的实验来解决这些问题。拟议的实验将结合新的方法来表示本地对象和场景区域的含义与高分辨率眼动跟踪测量知识的影响，在现实世界的场景中的注意力引导。本研究包括四个实验：（1）比较语境化和非语境化局部场景意义在注意引导中的作用。(2)评价局部场景意义与注意引导之间的因果关系。(3)测试场景意义引导在任务和观看时间上的通用性。(4)使用搜索目标模板比较场景中物理和语义特征的作用。该研究为研究场景意义的表征和场景中的注意引导提供了新的理论基础。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Real-world scenes comprise a blooming, buzzing confusion of information. Yet at any given moment, we can only perceive and understand a small portion of that information. What we see and understand is quite literally determined by where we look. But what determines where we look? This project seeks to answer this important question. The project investigates the idea that the meaning of a scene plays the key role in guiding our eyes. If our hypothesis is correct, then we should find that meaning predicts where people look. Such a result will advance scientific knowledge of how our brains and minds work. The results will also be useful to applied areas of computer science and engineering, contributing to increased US economic competitiveness. High-tech applications include virtual and augmented reality, artificial vision and gaze-based input systems, baggage screening, medical image assessment, satellite image analysis, and other computer-based vision systems. The project will also contribute to training of culture- and gender-diverse students and researchers in these high-tech and scientific fields, advancing the development of a diverse, globally competitive workforce. Attentional guidance during scene viewing draws on both the visual properties of the scene and its semantic content. Although the role of visual properties (e.g., physical salience) on attentional guidance has been extensively studied, far less is known about how the semantic content of a scene guides attention. Recent work in my lab indicates that the influence of physical saliency is reduced or even eliminated when semantic content is available to guide attention. These findings have opened up important new questions about how and when meaning guides attention in scenes. The central idea behind the current work is to address these questions with a set of targeted experiments. The proposed experiments will integrate new methods for representing the meaning of local objects and scene regions with high-resolution eyetracking to measure the influence of knowledge on attentional guidance in real-world scenes. The research includes experiments motivated by four goals: (1) To compare the roles of contextualized versus context-free local scene meaning in attentional guidance. (2) To evaluate the causal relationship between local scene meaning and attentional guidance. (3) To test the generality of guidance by scene meaning across tasks and viewing time. (4) To compare the roles of physical versus semantic features in scenes using search target templates. The research will establish the foundation for a new theoretical approach to the representation of scene meaning and attentional guidance in scenes. The ultimate objective is to develop a theory of attentional guidance in scenes based on guidance by meaning.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.