Visual and semantic similarity norms for a photographic image stimulus set containing recognizable objects, animals and scenes.

Visual and semantic similarity norms for a photographic image stimulus set containing recognizable objects, animals and scenes.
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DOI:
10.3758/s13428-021-01732-0
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发表时间:
2022-10
影响因子:
5.4
通讯作者:
Cowell, Rosemary A.
Cowell, Rosemary A.
中科院分区:
心理学2区
文献类型:
--
作者:
Jiang, Zhuohan;Sanders, D. Merika W.;Cowell, Rosemary A.

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我们收集了一组摄影图像,包括120个可识别的对象/动物和120个室内/室外场景的视觉和语义相似性规范。人类观察者通过亚马逊的Mechanical Turk对四类刺激(无生命物体,动物,室内场景和室外场景)中的图像对的相似性进行了评级。我们对收集的相似性评级进行了多维缩放(MDS),以可视化每个图像类别的感知相似性,用于视觉和语义评级。MDS解决方案揭示了每个类别中图像之间的预期相似性关系,沿着每个类别的视觉和语义相似性关系之间的直观差异。对MDS溶液进行的压力测试表明,MDS分析捕获了相似性数据中有意义的方差水平。这些刺激,相关的规范和命名数据是公开的,应该提供一个有用的资源,研究人员的视觉,记忆和概念知识,希望运行实验,使用参数化的刺激集。
We collected visual and semantic similarity norms for a set of photographic images comprising 120 recognizable objects/animals and 120 indoor/outdoor scenes. Human observers rated the similarity of pairs of images within four categories of stimulus - inanimate objects, animals, indoor scenes and outdoor scenes - via Amazon’s Mechanical Turk. We performed multi-dimensional scaling (MDS) on the collected similarity ratings to visualize the perceived similarity for each image category, for both visual and semantic ratings. The MDS solutions revealed the expected similarity relationships between images within each category, along with intuitively sensible differences between visual and semantic similarity relationships for each category. Stress tests performed on the MDS solutions indicated that the MDS analyses captured meaningful levels of variance in the similarity data. These stimuli, associated norms and naming data are made publicly available, and should provide a useful resource for researchers of vision, memory and conceptual knowledge wishing to run experiments using well-parameterized stimulus sets.
DOI: 10.1016/s0022-5371(76)90011-6
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