Key visual features for rapid categorization of animals in natural scenes.
Key visual features for rapid categorization of animals in natural scenes.
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DOI：
10.3389/fpsyg.2010.00021
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发表时间：
2010
影响因子：
3.8
通讯作者：
Fabre-Thorpe M
中科院分区：
文献类型：
--
作者：
Delorme A;Richard G;Fabre-Thorpe M
在快速分类任务中，决策可以基于诊断目标特征，或者它们可能需要激活对象的完整表示。根据任务要求，自上而下的期望启动特征检测器可能会降低选择单位的阈值或加快信息积累的速度。在本论文中，40名受试者进行了快速去/不去动物/非动物分类任务与400短暂闪现的自然场景，研究性能如何取决于物理场景的特点，目标配置，和诊断动物功能的存在或不存在。从准确度和速度两个方面评价性能，并绘制d′曲线作为反应时间（RT）的函数。这样的d′曲线给出了对整个受试者群体中所研究的特征和特性的处理动态的估计。全局图像特征，如颜色和亮度并不严重影响分类速度，虽然他们轻微影响准确性。全球的关键因素包括一个典型的动物姿势和动物/背景尺寸比的存在，表明粗糙的全球形式的作用。当动物处于典型姿势并且占据图像的20-30%时，准确性和速度的性能最佳。诊断性动物特征的存在是另一个关键因素。当诊断性动物部位（眼睛、嘴和四肢）缺失时，准确性（下降3.3-7.5%）和速度（中位RT增加7-16 ms）均显著受损。这些动物特征被证明会在很早的时候影响表现，当时只有15-25%的反应已经产生。与其他实验和建模研究一致，我们的研究结果支持基于关键中间特征和基于受试者专业知识的启动的动物快速诊断识别。
In speeded categorization tasks, decisions could be based on diagnostic target features or they may need the activation of complete representations of the object. Depending on task requirements, the priming of feature detectors through top–down expectation might lower the threshold of selective units or speed up the rate of information accumulation. In the present paper, 40 subjects performed a rapid go/no-go animal/non-animal categorization task with 400 briefly flashed natural scenes to study how performance depends on physical scene characteristics, target configuration, and the presence or absence of diagnostic animal features. Performance was evaluated both in terms of accuracy and speed and d′ curves were plotted as a function of reaction time (RT). Such d′ curves give an estimation of the processing dynamics for studied features and characteristics over the entire subject population. Global image characteristics such as color and brightness do not critically influence categorization speed, although they slightly influence accuracy. Global critical factors include the presence of a canonical animal posture and animal/background size ratio suggesting the role of coarse global form. Performance was best for both accuracy and speed, when the animal was in a typical posture and when it occupied about 20–30% of the image. The presence of diagnostic animal features was another critical factor. Performance was significantly impaired both in accuracy (drop 3.3–7.5%) and speed (median RT increase 7–16 ms) when diagnostic animal parts (eyes, mouth, and limbs) were missing. Such animal features were shown to influence performance very early when only 15–25% of the response had been produced. In agreement with other experimental and modeling studies, our results support fast diagnostic recognition of animals based on key intermediate features and priming based on the subject's expertise.
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DOI：
10.1037//0278-7393.26.2.470
发表时间：
2000-03-01
影响因子：
2.6
作者：
Cooper, EE;Wojan, TJ
通讯作者：
Wojan, TJ
影响因子：
9.2
作者：
Gegenfurtner, KR;Rieger, J
通讯作者：
Rieger, J
影响因子：
3.2
作者：
Fabre-Thorpe, M;Delorme, A;Thorpe, S
通讯作者：
Thorpe, S
影响因子：
3.4
作者：
Macé, MJM;Thorpe, SJ;Fabre-Thorpe, M
通讯作者：
Fabre-Thorpe, M
影响因子：
2.7
作者：
Mace, Marc J. -M.;Delorme, Arnaud;Fabre-Thorpe, Michele
通讯作者：
Fabre-Thorpe, Michele