瓶颈
计算机科学
视觉搜索
异步通信
人工智能
视觉对象识别的认知神经科学
对象(语法)
信息瓶颈法
视野
集合(抽象数据类型)
计算机视觉
视觉处理
感知
聚类分析
嵌入式系统
程序设计语言
神经科学
物理
光学
生物
计算机网络
出处
期刊:Oxford University Press eBooks
[Oxford University Press]
日期:2007-05-03
卷期号:: 99-119
被引量:709
标识
DOI:10.1093/acprof:oso/9780195189193.003.0008
摘要
Visual input is processed in parallel in the early stages of the visual system. Later, object recognition processes are also massively parallel, matching a visual object with a vast array of stored representation. A tight bottleneck in processing lies between these stages. It permits only one or a few visual objects at any one time to be submitted for recognition. That bottleneck limits performance on visual search tasks when an observer looks for one object in a field containing distracting objects. Guided Search is a model of the workings of that bottleneck. It proposes that a limited set of attributes, derived from early vision, can be used to guide the selection of visual objects. The bottleneck and recognition processes are modeled using an asynchronous version of a diffusion process. The current version (Guided Search 4.0) captures a range of empirical findings.
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