Eye movements during real-world visual search: A behavioral & computational study

现实世界视觉搜索期间的眼球运动：行为

基本信息

批准号：
8235077
负责人：
GREGORY J ZELINSKY
金额：
$ 30.31万
依托单位：
STATE UNIVERSITY NEW YORK STONY BROOK
依托单位国家：
美国
项目类别：
财政年份：
2002
资助国家：
美国
起止时间：
2002-09-05 至 2014-02-28
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8235077
关键词：
Accounting Address Affect Appearance Appetitive Behavior Attention Behavior Behavioral Behavioral Model Behavioral Research Categories Code Cognition Disorders Color Communities Complex Computer Simulation Data Diagnosis Disease Emergency Situation Emotional disorder Event Eye Movements Goals Human Image Joints Knowledge Label Laboratories Laboratory Study Lead Learning Left Literature Location Manuals Methods Modeling Molds Motor Movement Neurons Pattern Perceptual Disorders Population Process Public Health Research Research Personnel Retina Shapes Simulate Sorting - Cell Movement Staging Stimulus System Techniques Telephone Text Time Uncertainty Ursidae Family Visual Visual attention Visual impairment Work aged base behavior prediction computer studies effective therapy field study frontier gaze improved instrument interest neuropsychological oculomotor behavior payment response sample fixation theories tool visual search

Accounting Address Affect Appearance Appetitive Behavior Attention Behavior Behavioral Behavioral Model Behavioral Research Categories Code Cognition Disorders Color Communities Complex Computer Simulation Data Diagnosis Disease Emergency Situation Emotional disorder Event Eye Movements Goals Human Image Joints Knowledge Label Laboratories Laboratory Study Lead Learning Left Literature Location Manuals Methods Modeling Molds Motor Movement Neurons Pattern Perceptual Disorders Population Process Public Health Research Research Personnel Retina Shapes Simulate Sorting - Cell Movement Staging Stimulus System Techniques Telephone Text Time Uncertainty Ursidae Family Visual Visual attention Visual impairment Work aged base behavior prediction computer studies effective therapy field study frontier gaze improved instrument interest neuropsychological oculomotor behavior payment response sample fixation theories tool visual search

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项目摘要

PROJECT SUMMARY / ABSTRACT A joint behavioral/modeling approach is used to better understand the top-down constraints that guide overt visual attention in realistic contexts. In previous work we developed a biologically-plausible model of eye movements during search that used oriented and color-selective linear filters, population averaging over time, and an artificial retina to represent stimuli of arbitrary complexity. The simulated fixation-by-fixation behavior of this model compared well to human behavior, using stimuli ranging from Os and Qs to fully realistic scenes. However, this model was limited in that it had to be shown the target's exact appearance, and it could not exploit scene context to constrain attention to likely target locations. Consequently, it is largely unknown how people shift their attention as they look for scene constrained targets or targets that are defined categorically. These limitations are addressed in six studies. Studies 1-2 explore how people use scene context to narrow their search for a specific target in realistic scenes. A text precue provides information about the target's location in relation to a region of the scene ("in the field"; Study 1) or a scene landmark ("next to the blue building"; Study 2). Behavioral work quantifies the effects of these informational manipulations on search guidance; computational work implements the behavioral scene constraints and integrates them into the existing search model. Studies 3-6 address the relationship between search guidance and the level of detail in a target's description. Study 3 builds on previous work by designating targets either categorically (e.g., "find the teddy bear") or through use of a preview (e.g., a picture of a specific teddy bear), but increases the number of target categories to determine the boundary conditions on categorical search. Study 4 asks whether categorical targets are coded at the basic or subordinate levels, and Study 5 analyzes the distractors fixated during search to determine the features used to code these categorical targets. In Study 6 we use text labels to vary the degree of information in a target precue (e.g., a work boot target might be described as "footwear", a "boot", or a "tan work boot with red laces"). Study 7 describes the sorts of questions that can be asked once scene constraints and categorical target descriptions are integrated under a single theoretical framework, and Study 8 points to an entirely new research direction made possible by the modeling techniques that will be developed for this project. All of these studies are synergistic in that model predictions are used to guide behavioral studies, which in turn produce the data needed to refine the model and to make even more specific behavioral predictions. The project's long term objective is to obtain an understanding of how people allocate their overt visual attention in realistic contexts, specifically in terms of how partial information about an object's location in a scene or its appearance can be used to acquire targets in a search task. This understanding is expressed in the form of a computational model, one that can now use simple spatial relations and the visual features of learned target classes to acquire semantically-defined targets.

项目摘要 /摘要联合行为/建模方法用于更好地理解指导公开的自上而下的约束在现实情况下的视觉关注。在以前的工作中，我们开发了一种具有生物学性能的眼睛模型搜索过程中使用定向和颜色选择性线性过滤器的运动，人口随着时间的推移平均，和人工视网膜来表示任意复杂性的刺激。逐个固定行为的模拟固定行为该模型使用从OS和QS到完全逼真的场景的刺激，将其与人类行为进行了很好的比较。但是，该模型受到限制，因为必须显示目标的确切外观，并且无法利用它场景上下文，以限制对目标位置的关注。因此，在很大程度上不知道人们如何当他们寻找明确定义的场景限制目标或目标时，转移他们的注意力。这些局限性在六项研究中得到了解决。研究1-2探讨人们如何使用场景上下文缩小他们在现实场景中搜索特定目标。文本预处理提供有关目标位置的信息关于场景的区域（“在现场”；研究1）或场景地标（“蓝色建筑物旁边”；研究 2）。行为工作量化了这些信息操纵对搜索指导的影响；计算工作实现了行为场景的约束，并将其集成到现有搜索中模型。研究3-6解决了搜索指导与目标的细节水平之间的关系描述。研究3通过明确指定目标（例如，找到泰迪熊”）或通过使用预览（例如，特定泰迪熊的图片），但增加了目标的数量确定分类搜索边界条件的类别。研究4询问分类目标是否在基本或下属级别进行编码，研究5分析搜索过程中固定的干扰因素确定用于编码这些分类目标的功能。在研究6中，我们使用文本标签来改变程度目标预制中的信息（例如，工作引导目标可以描述为“鞋类”，“启动”或“ tan” 使用红色鞋带的工作引导”）。研究7描述了一旦场景限制，可以问的各种问题和分类目标描述是在单个理论框架下集成的，并研究了8点将通过为该项目开发的建模技术使全新的研究方向成为可能。所有这些研究都是协同作用的，因为该模型预测用于指导行为研究产生完善模型并做出更具体的行为预测所需的数据。这项目的长期目标是了解人们如何在现实的上下文，特别是关于如何在场景中的对象位置的部分信息外观可用于在搜索任务中获取目标。这种理解以一种形式表达计算模型，现在可以使用简单的空间关系和学习目标的视觉特征以获取语义定义的目标的类。