A novel hierarchical clustering algorithm for the analysis of 3D anthropometric data of the human head

Ellena, T, Subic, A, Mustafa El Bakri, H and Pang, T 2018, 'A novel hierarchical clustering algorithm for the analysis of 3D anthropometric data of the human head', Computer-Aided Design and Applications, vol. 15, no. 1, pp. 25-33.


Document type: Journal Article
Collection: Journal Articles

Title A novel hierarchical clustering algorithm for the analysis of 3D anthropometric data of the human head
Author(s) Ellena, T
Subic, A
Mustafa El Bakri, H
Pang, T
Year 2018
Journal name Computer-Aided Design and Applications
Volume number 15
Issue number 1
Start page 25
End page 33
Total pages 9
Publisher Taylor and Francis
Abstract In recent years, the use of 3D anthropometry for product design has become more appealing because of advances in mesh parameterisation, multivariate analyses and clustering algorithms. The purpose of this study was to introduce a new method for the clustering of 3D head scans. A novel hierarchical algorithm was developed, in which a squared Euclidean metric was used to assess the head shape similarity of participants. A linkage criterion based on the centroid distance was implemented, while clusters were created one after another in an enhanced manner. As a result, 95.0% of the studied sample was classified inside one of the four computed clusters. Compared to conventional hierarchical techniques, our method could classify a higher ratio of individuals into a smaller number of clusters, while still satisfying the same variation requirements within each cluster. The proposed method can provide meaningful information about the head shape variation within a population, and should encourage ergonomists to use 3D anthropometric data during the design process of head and facial gear.
Subject Mechanical Engineering not elsewhere classified
Keyword(s) 3D anthropometric data
clustering algorithm
hierarchical algorithm
DOI - identifier 10.1080/16864360.2017.1353727
Copyright notice © 2017 CAD Solutions, LLC
ISSN 1686-4360
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Created: Wed, 19 Sep 2018, 13:27:00 EST by Catalyst Administrator
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