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对全局场景属性的高级后效。

High-level aftereffects to global scene properties.

机构信息

Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.

出版信息

J Exp Psychol Hum Percept Perform. 2010 Dec;36(6):1430-42. doi: 10.1037/a0019058.

Abstract

Adaptation is ubiquitous in the human visual system, allowing recalibration to the statistical regularities of its input. Previous work has shown that global scene properties such as openness and mean depth are informative dimensions of natural scene variation useful for human and machine scene categorization (Greene & Oliva, 2009b; Oliva & Torralba, 2001). A visual system that rapidly categorizes scenes using such statistical regularities should be continuously updated, and therefore is prone to adaptation along these dimensions. Using a rapid serial visual presentation paradigm, we show aftereffects to several global scene properties (magnitude 8-21%). In addition, aftereffects were preserved when the test image was presented 10 degrees away from the adapted location, suggesting that the origin of these aftereffects is not solely due to low-level adaptation. We show systematic modulation of observers' basic-level scene categorization performances after adapting to a global property, suggesting a strong representational role of global properties in rapid scene categorization.

摘要

适应是人类视觉系统中普遍存在的现象,它允许对输入的统计规律进行重新校准。先前的研究表明,全局场景属性(如开放性和平均深度)是自然场景变化的信息维度,对人类和机器场景分类都很有用(Greene & Oliva,2009b;Oliva & Torralba,2001)。一个使用这些统计规律快速分类场景的视觉系统应该不断更新,因此很容易沿着这些维度产生适应。我们使用快速连续视觉呈现范式,展示了对几种全局场景属性(幅度为 8-21%)的后效。此外,当测试图像出现在适应位置 10 度之外时,后效仍然存在,这表明这些后效的产生不仅仅是由于低级别的适应。我们发现,在适应一个全局属性后,观察者的基本水平场景分类表现会出现系统的调制,这表明全局属性在快速场景分类中具有很强的代表性作用。

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