Please use this identifier to cite or link to this item:
Title: Predicting realistic and precise human body models under clothing based on orthogonal-view photos
Authors: Zhu, S
Mok, PY 
Keywords: Human body modelling
Computer graphics
Deformation technology
Artificial neural networks
Issue Date: 2015
Publisher: Elsevier
Source: Procedia manufacturing, 2015, v. 3, p. 3812-3819 How to cite?
Journal: Procedia manufacturing 
Abstract: Accurate and realistic digital human body models are required by many research applications, for example in the areas of ergonomics, clothing technology, and computer graphics. The already difficult research problem becomes more challenging if the individual subjects to be modelled are dressed in normal or loose-fit clothing. In this study, we present an intelligent two-phase method to customize 3D digital human body models based on two orthogonal-view photos of the customers. It integrates both image-based and example-based modelling techniques to create human body models for individual customers with precise body measurements and realistic appearance. It fills up the research gap of human model customization; without the need of taking body scan, any customers can create their 3D digital body models only based on their orthogonal-view photos in normal or loosefit clothing. Experimental results have shown that the proposed method can efficiently and accurately customize human models of diverse shapes, meeting the specific needs of the clothing industry.
Description: 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the Affiliated Conferences, AHFE 2015, Las Vegas, USA, 26-30 Jul 2015
ISSN: 2351-9789
DOI: 10.1016/j.promfg.2015.07.884
Rights: © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (
The following publication Zhu, S., & Mok, P. Y. (2015). Predicting realistic and precise human body models under clothing based on orthogonal-view photos. Procedia Manufacturing, 3, 3812-3819 is available at
Appears in Collections:Conference Paper

Files in This Item:
File Description SizeFormat 
Zhu_Predicting_Realistic_Precise.pdf610.65 kBAdobe PDFView/Open
View full-text via PolyU eLinks SFX Query
Show full item record
PIRA download icon_1.1View/Download Contents


Last Week
Last month
Citations as of Feb 14, 2019


Last Week
Last month
Citations as of Feb 18, 2019

Page view(s)

Last Week
Last month
Citations as of Feb 17, 2019


Citations as of Feb 17, 2019

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.