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A computational coding model for saliency detection in primary visual cortex 被引量:2

A computational coding model for saliency detection in primary visual cortex
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摘要 This study researches the coding model adaptive for information processing of the bottom-up attention mechanism.We constructed a coding model satisfying the neurobiological constraints of the primary visual cortex.By quantitatively changing the coding constraints,we carried out experiments on images used in cognitive psychology and natural image sets to compare the effects on the saliency detection performance.The experimental results statistically demonstrated that the encoding of invariant features and representation of overcomplete bases is advantageous to the bottom-up attention mechanism. This study researches the coding model adaptive for information processing of the bottom-up attention mechanism. We con- structed a coding model satisfying the neurobiological constraints of the primary visual cortex. By quantitatively changing the coding constraints, we carried out experiments on images used in cognitive psychology and natural image sets to compare the effects on the saliency detection performance. The experimental results statistically demonstrated that the encoding of invariant features and representation of overcomplete bases is advantageous to the bottom-up attention mechanism.
出处 《Chinese Science Bulletin》 SCIE CAS 2012年第30期3943-3952,共10页
基金 supported by the National Natural Science Foundation of China (60902058,60975078,61105119) Beijing Natural Science Foundation(4112047) Fundamental Research Funds for the Central Universities(2012JBM026,2011JBZ005)
关键词 初级视觉皮层 编码模型 检测性能 计算 注意机制 自底向上 模型自适应 神经生物学 visual attention, coding in primary visual cortex, saliency detection, invariant feature, overcomplete bases
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