Style Analysis Methodology: Identifying the Car Brand Design Trends through Hierarchical Clustering

Kyung Hoon Hyun, Ji-Hyun Lee, Mk Kim, Sulah Cho
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引用次数: 4

Abstract

This paper aims to identify car design trends within various automobile manufacturers by investigating two objectives: first, finding similarities between car styles among different car brands from various automobile manufacturers to specify unique car designs which lead the trend; second, identifying the consistency of the brand design characteristics through hierarchical clustering. To do that, Fourier decomposition was used to quantify the car design similarities between 120 cars from 23 different brands. The calculated similarity index is then compared with network centrality measures to identify the clustering of the car brands. The quantified style data then can be applied to accurately predict the design trend. Thus this study can contribute to identify car style trends for strategic design decisions.
风格分析方法:通过层次聚类识别汽车品牌设计趋势
本文旨在通过调查两个目标来确定各种汽车制造商内的汽车设计趋势:首先,从各种汽车制造商找到不同汽车品牌之间的汽车风格的相似性,以指定引领趋势的独特汽车设计;其次,通过层次聚类识别品牌设计特征的一致性。为了做到这一点,傅里叶分解被用来量化来自23个不同品牌的120辆汽车之间的汽车设计相似性。然后将计算出的相似度指数与网络中心性度量进行比较,以识别汽车品牌的聚类。量化的风格数据可以用来准确地预测设计趋势。因此,本研究有助于识别汽车风格趋势的战略设计决策。
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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