Making Tactile Textures with Predefined Affective Properties
Making Tactile Textures with Predefined Affective Properties
复制标题
DOI：
10.1109/t-affc.2013.21
复制
发表时间：
2014-01-01
影响因子：
11.2
通讯作者：
Henson, Brian
中科院分区：
文献类型：
--
作者：
Elkharraz, Galal;Thumfart, Stefan;Henson, Brian
开发了一种具有预定义情感特性的三维触觉纹理的设计和制造工艺。共制造了24种触觉纹理。使用机器视觉领域的纹理度量来表征触觉纹理的数字表示。为了获得情感评级，107名参与者触摸了这些纹理，但看不见它们，并在语义差异量表上对它们与自然、温暖、优雅、粗糙、简单和喜欢进行了评分。采用一种新的特征子集评价方法和偏最小二乘遗传算法将纹理测量与参与者的情感评分相关联。确定了六种与人类反应显著相关的措施，这些措施不太可能偶然发生。回归方程被用来选择48种新的触觉纹理，这些纹理是用混合算法合成的，当参与者触摸它们时，它们很可能在六个形容词中得分很高。新的纹理由参与者制作并打分。结果表明，回归方程具有较好的预测能力。这项工作的主要贡献是展示了一个过程，使用机器视觉方法和快速原型，可用于制造具有预定义情感属性的新触觉纹理。
A process for the design and manufacture of 3D tactile textures with predefined affective properties was developed. Twenty four tactile textures were manufactured. Texture measures from the domain of machine vision were used to characterize the digital representations of the tactile textures. To obtain affective ratings, the textures were touched, unseen, by 107 participants who scored them against natural, warm, elegant, rough, simple, and like, on a semantic differential scale. The texture measures were correlated with the participants' affective ratings using a novel feature subset evaluation method and a partial least squares genetic algorithm. Six measures were identified that are significantly correlated with human responses and are unlikely to have occurred by chance. Regression equations were used to select 48 new tactile textures that had been synthesized using mixing algorithms and which were likely to score highly against the six adjectives when touched by participants. The new textures were manufactured and rated by participants. It was found that the regression equations gave excellent predictive ability. The principal contribution of the work is the demonstration of a process, using machine vision methods and rapid prototyping, which can be used to make new tactile textures with predefined affective properties.