【摘要】 为探讨组成织物触觉质感多维感知属性空间的维度和意义,基于内隐记忆的语义描述实验,获得表征织物触觉质感的描述符,并研究各描述符出现的频率与平均次序间的关系。在此基础上,借鉴数据挖掘技术中聚类分析与因子分析相结合的算法,从认知科学角度确立表征织物触觉质感的空间维度。聚类分析结果表明,滑爽粗糙感、柔软硬挺感以及薄厚感可作为组成织物触觉质感属性空间的前3维,而第4维与黏涩感有关。通过因子分析证实,前5组因子的累计贡献率约达67.69%,即聚类分析得到的结果可解释触觉质感的主要差异。更多还原

【Abstract】 To study the primary components and the corresponding attributes of the tactile texture space of textile fabrics,this paper,based on the semantic experiments of implicit memory,obtained tactile texture descriptors and examined the relations between the frequency and average order of the descriptors.On this basis,the method of cluster and factor analysis in data mining is used to establish the perceptual dimensions of tactile textures from the perspective of cognitive science.The results from cluster analysis show that roughness-smoothness,hardness-softness and thinness-thickness are three dimensions of the tactile texture space.The fourth perceptual attribute would possibly be related to the viscidity.The results from factor analysis indicate that the cumulative contribution ratio of the five sets of factors reaches to about 67.69%,indicating that the results of the cluster analysis can explain the majority perceptual attributes of the tactile texture of fabrics.更多还原