A new parametric 3D human body modeling ...
Type de document :
Article dans une revue scientifique: Article original
URL permanente :
Titre :
A new parametric 3D human body modeling approach by using key position labeling and body parts segmentation
Auteur(s) :
Chi, Cheng [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Zeng, Xianyi [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Bruniaux, Pascal [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Tartare, Guillaume [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Jin, H. S. [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Zeng, Xianyi [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Bruniaux, Pascal [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Tartare, Guillaume [Auteur]
Génie des Matériaux Textiles - ULR 2461 [GEMTEX]
Jin, H. S. [Auteur]
Titre de la revue :
Textile Research Journal
Nom court de la revue :
Text. Res. J.
Numéro :
92
Pagination :
3653 - 3679
Date de publication :
2022-10
ISSN :
0040-5175
Mot(s)-clé(s) en anglais :
body part segmentation
key body position labeling
designer's knowledge
3D human body model
key body position labeling
designer's knowledge
3D human body model
Discipline(s) HAL :
Sciences de l'ingénieur [physics]
Résumé en anglais : [en]
The current three-dimensional human models used in the apparel industry are mostly rigid and lack semantic information on body positions and body parts. Therefore, it is difficult for designers to make accurate, fast and ...
Lire la suite >The current three-dimensional human models used in the apparel industry are mostly rigid and lack semantic information on body positions and body parts. Therefore, it is difficult for designers to make accurate, fast and effective designs from these models. This paper proposes a new parametric three-dimensional human body model based on key position labeling and optimized body parts segmentation. First, by using experts’ professional knowledge, we manually realize accurate human body data measurements as well as their interpretation and classification, and extract relevant human body features. After deep analysis, measured data irrelevant to body shape have been excluded by designers. Furthermore, the relation between body shapes and body features have been modeled. Second, based on this relational model, we label key positions on the corresponding three-dimensional body model obtained by scanning and segmenting the whole three-dimensional human body into semantically interpretable body parts. In this way, two databases have been created, enabling us to identify features of all segmented body parts, whose combination corresponds to the whole body shape. Third, for a specific consumer, his/her personalized three-dimensional human model can be obtained by taking a very few number of body measurements on himself/herself, making an appropriate combination of the identified body parts, and adjusting parameters of all involved body parts. By comparing the proposed labeled and segmented three-dimensional human model and the existing human models through a number of experiments, the proposed model leads to more relevant results with high accuracy and high visual quality related to real human body shapes.Lire moins >
Lire la suite >The current three-dimensional human models used in the apparel industry are mostly rigid and lack semantic information on body positions and body parts. Therefore, it is difficult for designers to make accurate, fast and effective designs from these models. This paper proposes a new parametric three-dimensional human body model based on key position labeling and optimized body parts segmentation. First, by using experts’ professional knowledge, we manually realize accurate human body data measurements as well as their interpretation and classification, and extract relevant human body features. After deep analysis, measured data irrelevant to body shape have been excluded by designers. Furthermore, the relation between body shapes and body features have been modeled. Second, based on this relational model, we label key positions on the corresponding three-dimensional body model obtained by scanning and segmenting the whole three-dimensional human body into semantically interpretable body parts. In this way, two databases have been created, enabling us to identify features of all segmented body parts, whose combination corresponds to the whole body shape. Third, for a specific consumer, his/her personalized three-dimensional human model can be obtained by taking a very few number of body measurements on himself/herself, making an appropriate combination of the identified body parts, and adjusting parameters of all involved body parts. By comparing the proposed labeled and segmented three-dimensional human model and the existing human models through a number of experiments, the proposed model leads to more relevant results with high accuracy and high visual quality related to real human body shapes.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
ENSAIT
Junia HEI
ENSAIT
Junia HEI
Collections :
Date de dépôt :
2023-06-20T12:02:32Z
2024-02-21T16:34:11Z
2024-02-21T16:34:11Z