The Texture Lexicon: Understanding the Categorization of Visual Texture Terms and Their Relationship to Texture Images

Nalini Bhushan, A. Ravishankar Rao, Gerald L. Lohse
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引用次数: 93

Abstract

Abstract In this paper we present the results of two experiments. The first is on the categorization of texture words in the English language. The goal was to determine whether there is a common basis for subjects' groupings of words related to visual texture, and if so, to identify the underlying dimensions used to categorize those words. Eleven major clusters were identified through hierarchical cluster analysis, ranging from ‘random’ to ‘repetitive’. These clusters remained intact in a multidimensional scaling solution. The stress for a three-dimensional solution obtained through multidimensional scaling was 0.18, meaning that 82% of the variance in the data is explained through the use of three dimensions. It appears that the major dimensions of texture descriptors are repetitive versus nonrepetitive; linearly oriented versus circularly oriented; and simple versus complex. In the second experiment we measured the strength of association between texture words and texture images. The goal was to determine whether there is any systematic correspondence between the domains of texture words and texture images. Pearson's coefficient of contingency, a measure of the strength of association, was found to be 0.63 for words corresponding to given images and 0.56 for images corresponding to given words. Thus the texture categories in the verbal space and those in the visual space are strongly tied. In sum, our two experiments show (a) that despite the tremendous variety in the words we have to describe textures, there is an underlying structure to the lexical space which can be derived from the experimental data; and (b) that the association between a category of words and a category of images was strongest when both categories represent the same underlying property. This suggests that subjects' organizations of texture terms are systematically tied to their organization of texture images.
纹理词典:理解视觉纹理术语的分类及其与纹理图像的关系
本文给出了两个实验的结果。第一部分是关于英语结构词的分类。目的是确定受试者对与视觉纹理相关的单词进行分组是否存在一个共同的基础,如果存在,则确定用于对这些单词进行分类的潜在维度。通过分层聚类分析确定了11个主要聚类,从“随机”到“重复”。这些集群在多维缩放解决方案中保持完整。通过多维缩放获得的三维解的应力为0.18,这意味着数据中82%的方差可以通过使用三维来解释。纹理描述符的主要维度似乎是重复的和非重复的;线性取向和圆形取向;简单和复杂。在第二个实验中,我们测量了纹理词和纹理图像之间的关联强度。目的是确定纹理词和纹理图像的域之间是否存在系统的对应关系。皮尔逊偶然性系数是一种衡量联想强度的指标,研究发现,单词对应给定图像的偶然性系数为0.63,图像对应给定单词的偶然性系数为0.56。因此,语言空间的纹理类别与视觉空间的纹理类别是紧密联系在一起的。总而言之,我们的两个实验表明:(a)尽管我们用来描述纹理的词汇种类繁多,但从实验数据中可以推导出词汇空间的基本结构;(b)一类单词和一类图像之间的关联在两个类别代表相同的潜在属性时是最强的。这表明受试者对纹理术语的组织与他们对纹理图像的组织有系统的联系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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