A Bayesian Framework for Crowding Effect

摘要：

In 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.

关键词： Crowding Effect Bayesian Model Generative Model Inferential Model

作者: Zhenbo Cheng Wenfeng Chen Tian Ran Zhidong Deng Xiaolan Fu

作者单位: State Key Laboratory on Intelligent Technology and Systems, Tsinghua National La oratory for Informa State Key Laboratory of Brain and Cognitive Science Institute of Psychology, Beijing 100101, China State Key Laboratory on Intelligent Technology and Systems, Tsinghua National La oratory for Informa

会议类型: 国际会议

会议名称: The 22nd China Control and Decision Conference(2010年中国控制与决策会议)

会议地点: 徐州

会议语种:英文

页码: 486-490

在线出版日期: 2010-05-26（万方平台首次上网日期，不代表论文的发表时间）