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定性和定量形状特征对跨视图变化的物体识别的贡献。

The contribution of qualitative and quantitative shape features to object recognition across changes of view.

作者信息

Liter J C

机构信息

University of California, Irvine, USA.

出版信息

Mem Cognit. 1998 Sep;26(5):1056-67. doi: 10.3758/bf03201183.

Abstract

Two experiments investigated the influence of qualitative and quantitative shape features on recognition of novel, four-component objects. Quantitatively different objects had different connection angles between the components. Qualitatively different objects had different connection angles and differently shaped components in some of the four positions. Old-new recognition declined less with changes of view for qualitatively different objects (Experiment 1). However, recognition of these objects was made to decline sharply with changes of view if subjects were biased to attend to the connection angles rather than the component shapes (Experiment 2), suggesting that the influence of different features depends on visual experience with those features. These results favor a feature-based model of shape representation that utilizes multiple feature types and that can rely on different features depending on particulars of the objects and the task.

摘要

两项实验研究了定性和定量形状特征对新型四组件物体识别的影响。定量不同的物体在组件之间具有不同的连接角度。定性不同的物体在四个位置中的某些位置具有不同的连接角度和形状不同的组件。对于定性不同的物体,新旧识别随着视角变化下降得较少(实验1)。然而,如果受试者倾向于关注连接角度而不是组件形状,那么这些物体的识别会随着视角变化而急剧下降(实验2),这表明不同特征的影响取决于对这些特征的视觉体验。这些结果支持一种基于特征的形状表征模型,该模型利用多种特征类型,并且可以根据物体和任务的具体情况依赖不同的特征。

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