Gosselin F, Schyns P G
Department of Psychology, University of Glasgow, 58 Hillhead Street, Glasgow G12 8QB, Scotland, UK.
Vision Res. 2001 Aug;41(17):2261-71. doi: 10.1016/s0042-6989(01)00097-9.
Everyday, people flexibly perform different categorizations of common faces, objects and scenes. Intuition and scattered evidence suggest that these categorizations require the use of different visual information from the input. However, there is no unifying method, based on the categorization performance of subjects, that can isolate the information used. To this end, we developed Bubbles, a general technique that can assign the credit of human categorization performance to specific visual information. To illustrate the technique, we applied Bubbles on three categorization tasks (gender, expressive or not and identity) on the same set of faces, with human and ideal observers to compare the features they used.
人们每天都会灵活地对常见的面孔、物体和场景进行不同的分类。直觉和零散的证据表明，这些分类需要使用来自输入的不同视觉信息。然而，基于受试者的分类表现，目前还没有一种统一的方法能够分离出所使用的信息。为此，我们开发了“气泡法”，这是一种通用技术，能够将人类分类表现的功劳归于特定的视觉信息。为了说明该技术，我们将“气泡法”应用于同一组面孔的三项分类任务（性别、是否有表情和身份），并与人类观察者和理想观察者进行比较，以了解他们所使用的特征。
