Virtual mannequins and garment parametrization

Maria Kulinska, Pascal Bruniaux, Antti Ainamo, Xianyi Zeng, Yan Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

3 Citations (Scopus)


Continuing earlier work, this paper conceptualizes an adaptive methodology to parametrically design garments on virtual mannequins for a target population. The target population is composed of 485 women scanned in 2006 by IFTH, the French research institute and it has been classified into three clusters which give us three parametric mannequins. In this paper, each of these mannequins is associated with a process of parametric garment design and its grading based on differences in stature, volume, and ease allowance. We show how neck and armhole lines are pivotal for draping the garment on a mannequin. We find clear benefits in terms of facilitation and improvement in our method of 3D parametrization providing design rules for specifying neck line and armhole line design. We expect this method of 3D parametric garment design to facilitate and improve not only the specific lines under analysis but also the design process as a whole, and hence to assure the good consumer fit.

Original languageEnglish
Title of host publicationUncertainty Modelling in Knowledge Engineering and Decision Making - Proceedings of the 12th International FLINS Conference, FLINS 2016
Number of pages6
ISBN (Electronic)9789813146969
Publication statusPublished - 2016
MoE publication typeA4 Article in a conference publication
EventInternational Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference - Roubaix, France
Duration: 24 Aug 201626 Aug 2016
Conference number: 12

Publication series

NameWorld Scientific Proceedings Series on Computer Engineering and Information Science


ConferenceInternational Fuzzy Logic and Intelligent Technologies in Nuclear Science Conference
Abbreviated titleFLINS


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