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Rapid scene categorization: From coarse peripheral vision to fine central vision.
Vision Research ( IF 1.5 ) Pub Date : 2020-04-04 , DOI: 10.1016/j.visres.2020.02.008
Audrey Trouilloud 1 , Louise Kauffmann 2 , Alexia Roux-Sibilon 1 , Pauline Rossel 1 , Muriel Boucart 3 , Martial Mermillod 1 , Carole Peyrin 1
Affiliation  

Studies on scene perception have shown that the rapid extraction of low spatial frequencies (LSF) allows a coarse parsing of the scene, prior to the analysis of high spatial frequencies (HSF) containing details. Many studies suggest that scene gist recognition can be achieved with only the low resolution of peripheral vision. Our study investigated the advantage of peripheral vision on central vision during a scene categorization task (indoor vs. outdoor). In Experiment 1, we used large scene photographs from which we built one central disk and four circular rings of different eccentricities. The central disk either contained or not an object semantically related to the scene category. Results showed better categorization performances for the peripheral rings, despite the presence of an object in central vision that was semantically related to the scene category that significantly improved categorization performances. In Experiment 2, the central disk and rings were assembled from Central to Peripheral vision (CtP sequence) or from Peripheral to Central vision (PtC sequence). Results revealed better performances for PtC than CtP sequences, except when no central object was present under rapid categorization constraints. As Experiment 3 suggested that the PtC advantage was not explained by a reduction of the visibility of the object in the central disk by the surrounding peripheral rings (CtP sequence), results are interpreted in the context of a predominant coarse-to-fine processing during scene categorization, with greater efficiency and utility of coarse peripheral vision relative to fine central vision during rapid scene categorization.

中文翻译:

快速的场景分类:从粗糙的周边视觉到精细的中央视觉。

对场景感知的研究表明,在分析包含细节的高空间频率(HSF)之前,快速提取低空间频率(LSF)可以对场景进行粗略的解析。许多研究表明,只有低分辨率的周边视觉才能实现场景要点识别。我们的研究调查了场景分类任务(室内与室外)中外围视觉对中央视觉的优势。在实验1中,我们使用了大场景照片,从中我们构建了一个中心盘和四个不同偏心率的圆环。中央磁盘包含或不包含与场景类别在语义上相关的对象。结果显示,外围环的分类性能更好,尽管中央视觉中存在与场景类别在语义上相关的对象,但可以显着改善分类性能。在实验2中,从中央到周边视觉(CtP序列)或从周边到中央视觉(PtC序列)组装了中心盘和环。结果表明,与PtC序列相比,PtC的性能更好,除非在快速分类约束下没有中心对象存在。由于实验3提出PtC的优势并没有通过周围的外围环(CtP序列)降低中心盘中对象的可见性来解释,因此在进行粗加工到精加工的过程中解释了结果场景分类
更新日期:2020-04-04
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