CumInCAD is a Cumulative Index about publications in Computer Aided Architectural Design
supported by the sibling associations ACADIA, CAADRIA, eCAADe, SIGraDi, ASCAAD and CAAD futures

id caadria2014_116
authors Hyun, Kyung Hoon; Ji-Hyun Lee, Minki Kim and Sulah Cho
year 2014
title Style Analysis Methodology: Identifying the Car Brand Design Trends through Hierarchical Clustering
source Rethinking Comprehensive Design: Speculative Counterculture, Proceedings of the 19th International Conference on Computer-Aided Architectural Design Research in Asia (CAADRIA 2014) / Kyoto 14-16 May 2014, pp. 327336
summary 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.
keywords Style analysis; design trend; brand cluster; brand identity
series CAADRIA
email hellohoon@kaist.ac.kr
full text file.pdf (1,550,256 bytes)
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