Metrics analysis of tactile perceptual space based on improved NMDS for leather textures  

基于INMDS算法的皮革纹理触觉感知空间度量分析

作　　者：Huang Gewen He Cong Wu Juan Wang Fei 黄戈文;何聪;吴涓;王飞(东南大学仪器科学与工程学院,南京210096)

机构地区：[1]School of Instrument Science and Engineering,Southeast University,Nanjing 210096,China

出　　处：《Journal of Southeast University(English Edition)》2022年第1期49-55,共7页东南大学学报（英文版）

基　　金：The National Key R&D Program of China(No.2018AAA0103001);the National Natural Science Foundation of China(No.62073073)。

摘　　要：To solve the fuzzy and unstable tactile similarity relationship between some sample points in the perception experiment,an improved non-metric multidimensional scaling(INMDS)is proposed in this paper.In view of the inconsistency of each sample s contribution,the maximum marginal decision when constructing the perception space to describe the tactile perception characteristics is also proposed.The corresponding constraints are set according to the degree of similarity,and controlling the relaxation variable factor is proposed to optimize the perception dimension and coordinate measurement.The effectiveness of the INMDS algorithm is verified by two perception experiments.The results show that compared with the metric multidimensional scaling(MDS)and non-metric multidimensional scaling(NMDS)algorithms,the perceptual space constructed by INMDS can more accurately reflect the difference relationship between different leather sample points perceived by people.Moreover,the relative position of sample points in the perceptual space is more consistent with subjective perception results.为了解决感知实验中样本点间的触觉相似度关系模糊且不稳定的问题,提出了一种改进的非度量型多维尺度变换(INMDS)算法.在构建描述触觉感知特征的感知空间时,引入距离相近最大边际决策.根据相似度大小设定相应的约束条件,通过控制松弛变量因子来优化感知维度和坐标度量,并利用2个感知实验来验证INMDS算法的有效性.结果表明,与度量型多维尺度变换(MDS)和非度量型多维尺度变换(NMDS)算法相比,所提方法构建的感知空间能更准确地反映人所感知的不同皮革样本点的差异度关系,且感知空间中样本点的相对位置与主观感知结果更加一致.

关 键 词：HAPTIC tactile perception perceptual space non-metric multidimensional scaling 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]