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视觉搜索、视觉信息流和视觉架构。

Visual search, visual streams, and visual architectures.

作者信息

Green M

机构信息

Computer Studies Programme, Trent University, Peterborough, Ontario, Canada.

出版信息

Percept Psychophys. 1991 Oct;50(4):388-403. doi: 10.3758/bf03212232.

Abstract

Most psychological, physiological, and computational models of early vision suggest that retinal information is divided into a parallel set of feature modules. The dominant theories of visual search assume that these modules form a "blackboard" architecture: a set of independent representations that communicate only through a central processor. A review of research shows that blackboard-based theories, such as feature-integration theory, cannot easily explain the existing data. The experimental evidence is more consistent with a "network" architecture, which stresses that: (1) feature modules are directly connected to one another, (2) features and their locations are represented together, (3) feature detection and integration are not distinct processing stages, and (4) no executive control process, such as focal attention, is needed to integrate features. Attention is not a spotlight that synthesizes objects from raw features. Instead, it is better to conceptualize attention as an aperture which masks irrelevant visual information.

摘要

大多数早期视觉的心理学、生理学和计算模型表明,视网膜信息被划分为一组并行的特征模块。视觉搜索的主流理论假定这些模块构成一种“黑板”架构:一组仅通过中央处理器进行通信的独立表征。一项研究综述表明,诸如特征整合理论等基于黑板的理论难以轻松解释现有数据。实验证据更符合一种“网络”架构,该架构强调:(1)特征模块彼此直接相连;(2)特征及其位置共同呈现;(3)特征检测与整合并非不同的处理阶段;(4)整合特征无需诸如焦点注意之类的执行控制过程。注意并非是一个从原始特征合成物体的聚光灯。相反,将注意概念化为一个遮蔽不相关视觉信息的小孔更为恰当。

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