PSYCH OpenIR  > 中国科学院心理研究所回溯数据库(1956-2010)
A Bayesian framework for crowding effect
Zhenbo Cheng; Wenfeng Chen; Tian Ran; Zhidong Deng; Xiaolan Fu
2010
Conference NameControl and Decision Conference (CCDC), 2010 Chinese
Conference Date2010
Conference PlaceXuzhou
PublisherIEEE
AbstractIn crowding, neighboring distractors impair the visual perception of a presented ta get. We study influences by the configuration of distractors on the bias to perceive the orientation of a target. Our results show that: (a) when distractors are similar to each other but different from target, crowding is decreased; (b) when distractors form a subjective contour, crowding is also reduced. These results illustrate that crowding is weak whenever the target stands out from the context and strong when the target is grouped into the context as a part of a global percept. In addition, we show how a Bayesian model, based on the principle of spatial resolution of attention that is modulated by the large size of receptive fields, can account for the behavioral data.
KeywordBayesian Model Crowding Effect Generative Model Inferential Model
Subject Area认知心理学
ISBN978-1-4244-5181-4
Indexed ByEI
Language英语
Document Type会议论文
Identifierhttp://ir.psych.ac.cn/handle/311026/10116
Collection中国科学院心理研究所回溯数据库(1956-2010)
Recommended Citation
GB/T 7714
Zhenbo Cheng,Wenfeng Chen,Tian Ran,et al. A Bayesian framework for crowding effect[C]:IEEE,2010.
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