Making Sense of Visual Search

描述（由申请人提供）：在我们的日常生活中，我们寻找我们的钥匙，在人群中寻找朋友，并试图在我们的遥控器上找到一个按钮。视觉搜索也是许多应用的重要组成部分，包括在乳房x光检查中搜索可能的肿瘤，或在行李x光检查中搜索威胁。人们对搜索进行了30年的深入研究，但结果仍然令人困惑。有些搜索很容易，即使目标出现在许多“干扰”项目的背景下。其他搜索在有许多干扰物的情况下变得相当困难，即使目标和干扰物截然不同。我们缺乏一个计算模型来预测哪些搜索是容易的，哪些是困难的，或者对任意显示的搜索性能进行定量预测。本研究的总体目标是更好地理解视觉搜索，基于周边视觉的能力是搜索性能的基本约束。周边视觉能够在周边快速检测到目标（目标似乎“突然出现”），并引导眼球运动，直到观察者最终找到目标。提出的工作建立在最近的周边视觉建模的基础上。这些最近的结果表明，周边视觉处理的不是单个项目，而是相当大的局部“斑块”，它以一组丰富的汇总统计数据表示（Balas, Nakano, & Rosenholtz, 2009）。拟议中的研究有两个相互交织的目的。目标1是开发和测试视觉搜索模型，该模型基于搜索受到包含目标（和许多干扰物）和仅包含干扰物的外围斑块的可辨别性约束的假设。特别是，Rosenholtz博士将研究搜索性能在多大程度上可以通过以下方式来预测：(1)单个项目(2)更大、更拥挤的区域。(3)基于目标存在斑块和目标缺失斑块的汇总统计表示预测其可判别性；(4)寻找目标所需注视的定量模型。目的2是测试广泛的搜索现象是否可以由单一的周边视觉机制来解释。特别是，Rosenholtz博士将研究：(1)搜索不对称的优势，例如，在“O”中搜索“Q”比在“Q”中搜索“O”更容易；(2)通过单个特征、特征的组合以及基本特征的配置来寻找与干扰物不同的目标之间的差异；(3)关于什么是可以引导搜索的“基本功能”的说法有些令人费解；(4)分组对视觉搜索的影响。

DESCRIPTION (provided by applicant): In our daily lives, we search for our keys, look for a friend in a crowd, and try to find a button on our remote control. Visual search is an important part of many applications, as well, including search for a possible tumor in a mammogram, or search for a threat in a baggage x-ray. Search has been studied intensely for 30 years, but the results remain puzzling. Some searches are easy, even when the target appears against a background of many "distractor" items. Other searches become quite difficult with many distractors, even when the target and distractors are quite distinct. We lack a computational model that can predict which searches will be easy or hard, or make quantitative predictions of search performance for arbitrary displays. The overall goal of the proposed research is to better understand visual search based on the insight that the capabilities of peripheral vision provide a fundamental constraint on search performance. Peripheral vision enables fast target detection in the periphery (the target seems to "pop out"), and guides eye movements until, ultimately, the observer finds the target. The proposed work builds on recent modeling of peripheral vision. These recent results suggest that peripheral vision processes not individual items, but rather sizable local "patches," which it represents in terms of a rich set of summary statistics (Balas, Nakano, & Rosenholtz, 2009). The proposed research has two intertwined aims. Aim 1 is to develop and test models of visual search based on the hypothesis that search is constrained by the discriminability of peripheral patches containing a target (and a number of distractors), and those containing only distractors. In particular, Dr. Rosenholtz will examine the extent to which search performance can be predicted by: Peripheral discriminability of (1) individual items (2) larger, crowded patches. (3) Predicted discriminability of target present vs. target absent patches based upon their summary statistic representation; (4) A quantitative model of the fixations required to find a target. Aim 2 is to test whether a wide range of search phenomena can be accounted for by a single mechanism of peripheral vision. In particular, Dr. Rosenholtz will examine: (1) The predominance of search asymmetries, e.g. that it is easier to search for a 'Q' among 'O's than for an 'O' among 'Q's; (2) Differences between search for a target differing from distractors by a single feature, by a conjunction of features, and by a configuration of basic features; (3) Somewhat puzzling accounts of what constitutes a "basic feature" that can guide search; (4) The effects of grouping on visual search.