Independent mechanisms for processing local contour features and global shape.

模式识别(心理学) 灵敏度(控制系统) 人工智能 特征(语言学) 视觉搜索 对象(语法) 数学 计算机科学 计算机视觉 语言学 哲学 电子工程 工程类
作者
Nicholas Baker,Philip J. Kellman
出处
期刊:Journal of Experimental Psychology: General 卷期号:152 (5): 1502-1526 被引量:1
标识
DOI:10.1037/xge0001349
摘要

The visual system can extract the global shape of an object from highly variable local contour features. We propose that there are separate systems for processing local and global shape. These systems are independent and process information differently. Global shape encoding accurately represents the form of low-frequency contour variations, whereas the local system encodes only summary statistics that describe typical features of high-frequency elements. In Experiments 1-4, we tested this hypothesis by obtaining same/different judgments for shapes that differed in local features, global features, or both. We found low sensitivity to changed local features that shared the same summary statistics, and no advantage in sensitivity for shapes that differed in both local and global features compared to shapes that differed only in global features. This sensitivity difference persisted when physical contour differences were equated and when shape feature sizes and exposure durations were increased. In Experiment 5, we compared sensitivity to sets of local contour features with matched or unmatched statistical properties. Sensitivity was higher for unmatched statistical properties than for properties sampled from the same statistical distribution. Experiment 6 directly tested our hypothesis of independent local and global systems using visual search. Search based on either local or global shape differences produced pop-out effects, but search for a target based on a conjunction of local and global differences required focal attention. These findings support the notion that separate mechanisms process local and global contour information and that the kinds of information these mechanisms encode are fundamentally different. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
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