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全局图像属性不会引导视觉搜索。

Global image properties do not guide visual search.

作者信息

Greene Michelle R, Wolfe Jeremy M

机构信息

Brigham and Women's Hospital, USA.

出版信息

J Vis. 2011 May 24;11(6):10.1167/11.6.18 18. doi: 10.1167/11.6.18.

Abstract

While basic visual features such as color, motion, and orientation can guide attention, it is likely that additional features guide search for objects in real-world scenes. Recent work has shown that human observers efficiently extract global scene properties such as mean depth or navigability from a brief glance at a single scene (M. R. Greene & A. Oliva, 2009a, 2009b). Can human observers also efficiently search for an image possessing a particular global scene property among other images lacking that property? Observers searched for scene image targets defined by global properties of naturalness, transience, navigability, and mean depth. All produced inefficient search. Search efficiency for a property was not correlated with its classification threshold time from M. R. Greene and A. Oliva (2009b). Differences in search efficiency between properties can be partially explained by low-level visual features that are correlated with the global property. Overall, while global scene properties can be rapidly classified from a single image, it does not appear to be possible to use those properties to guide attention to one of several images.

摘要

虽然诸如颜色、运动和方向等基本视觉特征可以引导注意力,但很可能还有其他特征在现实场景中引导对物体的搜索。最近的研究表明,人类观察者只需短暂瞥一眼单个场景,就能有效地提取诸如平均深度或可导航性等全局场景属性(M. R. 格林和A. 奥利瓦,2009a,2009b)。人类观察者能否也在缺乏特定全局场景属性的其他图像中有效地搜索具有该属性的图像呢?观察者搜索了由自然性、短暂性、可导航性和平均深度等全局属性定义的场景图像目标。所有搜索结果都效率低下。一种属性的搜索效率与其从M. R. 格林和A. 奥利瓦(2009b)处获得的分类阈值时间无关。属性之间搜索效率的差异可以部分由与全局属性相关的低层次视觉特征来解释。总体而言,虽然可以从单个图像中快速分类全局场景属性,但似乎无法利用这些属性将注意力引导到多个图像中的某一个上。

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