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相似性与分类:从视觉到触觉

Similarity and categorization: from vision to touch.

作者信息

Gaissert Nina, Bülthoff Heinrich H, Wallraven Christian

机构信息

Max Planck Institute for Biological Cybernetics, Tübingen, Spemannstr. 38, 72076 Tübingen, Germany.

出版信息

Acta Psychol (Amst). 2011 Sep;138(1):219-30. doi: 10.1016/j.actpsy.2011.06.007. Epub 2011 Jul 14.

DOI:10.1016/j.actpsy.2011.06.007
PMID:21752344
Abstract

Even though human perceptual development relies on combining multiple modalities, most categorization studies so far have focused on the visual modality. To better understand the mechanisms underlying multisensory categorization, we analyzed visual and haptic perceptual spaces and compared them with human categorization behavior. As stimuli we used a three-dimensional object space of complex, parametrically-defined objects. First, we gathered similarity ratings for all objects and analyzed the perceptual spaces of both modalities using multidimensional scaling analysis. Next, we performed three different categorization tasks which are representative of every-day learning scenarios: in a fully unconstrained task, objects were freely categorized, in a semi-constrained task, exactly three groups had to be created, whereas in a constrained task, participants received three prototype objects and had to assign all other objects accordingly. We found that the haptic modality was on par with the visual modality both in recovering the topology of the physical space and in solving the categorization tasks. We also found that within-category similarity was consistently higher than across-category similarity for all categorization tasks and thus show how perceptual spaces based on similarity can explain visual and haptic object categorization. Our results suggest that both modalities employ similar processes in forming categories of complex objects.

摘要

尽管人类的感知发展依赖于多种感觉模态的结合,但迄今为止,大多数分类研究都集中在视觉模态上。为了更好地理解多感官分类背后的机制,我们分析了视觉和触觉感知空间,并将它们与人类的分类行为进行了比较。作为刺激物,我们使用了一个由复杂的、参数定义的物体组成的三维物体空间。首先,我们收集了所有物体的相似性评级,并使用多维尺度分析来分析两种模态的感知空间。接下来,我们进行了三种不同的分类任务,这些任务代表了日常学习场景:在完全无约束的任务中,物体被自由分类;在半约束任务中,必须精确地创建三组;而在约束任务中,参与者会收到三个原型物体,并必须相应地分配所有其他物体。我们发现,在恢复物理空间的拓扑结构和解决分类任务方面,触觉模态与视觉模态相当。我们还发现,在所有分类任务中,类别内的相似性始终高于类别间的相似性,从而展示了基于相似性的感知空间如何能够解释视觉和触觉物体分类。我们的结果表明,两种模态在形成复杂物体类别时采用了相似的过程。

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