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

现实世界的场景包含了大量的、嗡嗡作响的信息混乱。然而，在任何给定的时刻，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东西实际上是由我们所看的地方决定的。但是，是什么决定了我们的视线呢？这个项目试图回答这个重要的问题。该项目研究了场景的意义在引导我们的眼睛方面起着关键作用的想法。如果我们的假设是正确的，那么我们应该发现，意义预测了人们的视线。这样的结果将促进对我们的大脑和思维如何工作的科学知识的发展。研究结果还将有益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、行李检查、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不同文化和性别的学生和研究人员，促进发展一支具有全球竞争力的多样化劳动力队伍。在场景观看过程中的注意引导利用了场景的视觉属性及其语义内容。虽然视觉特性(例如，物理突显)在注意引导中的作用已经被广泛研究，但关于场景的语义内容如何引导注意的了解要少得多。我的实验室最近的研究表明，当语义内容可用于引导注意力时，身体显著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。建议的实验将结合高分辨率眼动来表示局部物体和场景区域的意义的新方法，以衡量知识对现实世界场景中注意指导的影响。本研究包括四个实验：(1)比较情境化和非情境化的局部场景意义在注意指导中的作用。(2)考察注意引导与局部情景意义之间的因果关系。(3)考察不同任务、不同观看时间的情景意义引导的通用性。(4)使用搜索目标模板比较物理特征和语义特征在场景中的作用。本研究将为场景意义表征和注意引导的新理论研究奠定基础。最终目标是开发一种基于意义指导的场景注意力指导理论。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.