Semantic Guidance of Visual Attention

视觉注意力的语义指导

• 批准号: 8389903
• 负责人: Marc Pomplun
• 金额: $ 21.23万
• 依托单位: UNIVERSITY OF MASSACHUSETTS BOSTON
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-12-01 至 2014-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8389903
• 关键词: Address; Alzheimer' s Disease; Attention; Behavioral; Cognitive; Color; Computer Simulation; Data; Databases; Dependency; Diagnosis; Disease; Eye Movements; Future; Image; Impairment; Individual; Investigation; Judgment; Knowledge; Label; Maps; Measures; Methodology; Modeling; Process; Research; Research Personnel; Semantics; Shapes; Uncertainty; Visual; Visual attention; Work; base; clinical application; gaze; neurophysiology; novel; object perception; preference; tool

DESCRIPTION (provided by applicant): Our visual world does not only consist of low-level features such as color or contrast, but it also contains high- level features such as the meaning of objects and the semantic relations among them. While it has been shown that low-level features in real-world scenes guide eye movements during scene inspection and search, the influence of semantic similarity among scene objects on eye movements in such situations has not been investigated. The proposed project will study guidance of eye movements by semantic similarity between objects during real-world scene inspection and search using a novel methodology that was developed in preliminary studies. By selecting scenes from the LabelMe object-annotated image database and applying Latent Semantic Analysis (LSA) to the object labels, we generated semantic saliency maps of real-world scenes based on the semantic similarity of scene objects to the currently fixated object or the search target. An ROC analysis of these maps as predictors of subjects' gaze transitions between objects during scene inspection revealed a preference for transitions to objects that were semantically similar to the currently inspected one (transitional semantic guidance). Furthermore, during the course of a scene search, subjects' eye movements were progressively guided toward objects that were semantically similar to the search target (target-induced semantic guidance). These preliminary findings demonstrate substantial semantic guidance of eye movements in real-world scenes and show its importance for understanding real-world attentional control. The proposed project will build on these results to establish a new field of research and a broader model of attentional control in real-world scenes. First, it will investigate two potential factors that control semantic guidance, namely the observer's individual semantic space (Study 1) and the semantic consistency of the visual scene (Study 2). Second, the project will examine the ecological function of two aspects of semantic guidance: the finding of transitional semantic guidance during scene inspection (Study 3) and the observation of a gradual increase in target-induced semantic guidance during the course of a search process (Study 4). The results of Studies 1 to 4 will direct the course of future behavioral and neurophysiological investigations of semantic guidance. Moreover, the first, basic understanding of semantic guidance developed in these studies will be used in Study 5 to devise a computational model of this knowledge and combine it with traditional models of attentional control that are limited to the influence of low-level visual features. The resulting two-level attentional control model will advance the field by helping researchers to form a more comprehensive view of visual attention in real-world scenes.

描述（由申请人提供）：我们的视觉世界不仅由诸如颜色或对比的低级特征组成，而且还包含高级特征，例如对象的含义以及它们之间的语义关系。虽然已经表明，在现实世界场景中的低水平特征指导了场景检查和搜索过程中的眼睛运动，但尚未研究场景对象之间语义相似性对这种情况下眼睛运动的影响。拟议的项目将通过在初步研究中开发的新方法来研究对象之间的语义相似性来研究眼球运动的指导。通过从标签对象注销的图像数据库中选择场景并将潜在语义分析（LSA）应用于对象标签，我们根据场景对象的语义相似性在当前固定的对象或搜索中生成了现实世界场景的语义显着性图目标。对这些地图的ROC分析是对象在场景检查过程中对象之间的凝视过渡的预测指标，这表明对与当前检查的对象相似的对象（过渡语义指导）偏爱过渡。此外，在场景搜索过程中，受试者的眼睛运动逐渐引导到与搜索目标（目标引起的语义指导）上相似的对象。这些初步发现表明了对现实世界中眼动的大量语义指导，并显示了其对理解现实世界注意控制的重要性。拟议的项目将建立在这些结果的基础上，以建立一个新的研究领域和在现实场景中更广泛的注意力控制模型。首先，它将研究控制语义指导的两个潜在因素，即观察者的单个语义空间（研究1）和视觉场景的语义一致性（研究2）。其次，该项目将研究语义指导的两个方面的生态功能：在场景检查期间发现过渡性语义指导（研究3）以及在搜索过程中观察目标引起的语义指导的逐渐增加（研究4）。研究1至4的结果将指导语义指导的未来行为和神经生理研究的过程。此外，在研究5中将使用对这些研究中开发的语义指导的第一个基本理解，以设计这种知识的计算模型，并将其与传统的注意力控制模型相结合，这些模型仅限于低级视觉特征的影响。由此产生的两级注意力控制模型将通过帮助研究人员在现实世界中对视觉关注的更全面的看法来推进该领域。