Title: Application of massive 3D head and facial scan datasets in ergonomic head-product design

Authors: Wonsup Lee; Xiaopeng Yang; Hayoung Jung; Heecheon You; Lyè Goto; Johan F.M. Molenbroek; Richard H.M. Goossens

Addresses: Faculty of Industrial Design Engineering, Delft University of Technology, Delft, 2628 CE, The Netherlands ' Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Gyeongbuk, 790-784, South Korea ' Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Gyeongbuk, 790-784, South Korea ' Department of Industrial and Management Engineering, Pohang University of Science and Technology, Pohang, Gyeongbuk, 790-784, South Korea ' Landbergstraat 15, Delft, 2628 CE, The Netherlands ' Landbergstraat 15, Delft, 2628 CE, The Netherlands ' Faculty of Industrial Design Engineering, Delft University of Technology, Delft, 2628 CE, The Netherlands

Abstract: 3D human body scan datasets have been collected and various techniques of post-processing, size and shape analysis, and applications in product design have been introduced. This paper is aimed to introduce techniques and cases of head-product design studies based on massive 3D head scan datasets. 3D scan datasets of the head, face and ear were collected and post-processed by editing, landmarking, alignment and measurement. For useful application of the 3D head scan datasets in head-product designs, we applied several analysis techniques such as development of a sizing system, selection of representative models, analysis of shape variation based on template-registered 3D scans and analysis of virtual fit. This paper can help understand an overview of techniques regarding massive 3D scan datasets and their applications to ergonomic product design.

Keywords: 3D scan dataset; head-product design; sizing analysis; shape variation; optimal design technique.

DOI: 10.1504/IJDH.2016.084592

International Journal of the Digital Human, 2016 Vol.1 No.4, pp.344 - 360

Available online: 31 May 2017 *

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