Personalized 3D mannequin reconstruction based on 3D scanning

Purpose Currently, a common method of reconstructing mannequin is based on the body measurements or body features, which only preserve the body size lacking of the accurate body geometric shape information. However, the same human body measurement does not equal to the same body shape. This may result in an unfit garment for the target human body. The purpose of this paper is to propose a novel scanning-based pipeline to reconstruct the personalized mannequin, which preserves both body size and body shape information. Design/methodology/approach The authors first capture the body of a subject via 3D scanning, and a statistical body model is fit to the scanned data. This results in a skinned articulated model of the subject. The scanned body is then adjusted to be pose-symmetric via linear blending skinning. The mannequin part is then extracted. Finally, a slice-based method is proposed to generate a shape-symmetric 3D mannequin. Findings A personalized 3D mannequin can be reconstructed from the scanned body. Compared to conventional methods, the method can preserve both the size and shape of the original scanned body. The reconstructed mannequin can be imported directly into the apparel CAD software. The proposed method provides a step for digitizing the apparel manufacturing. Originality/value Compared to the conventional methods, the main advantage of the authors’ system is that the authors can preserve both size and geometry of the original scanned body. The main contributions of this paper are as follows: decompose the process of the mannequin reconstruction into pose symmetry and shape symmetry; propose a novel scanning-based pipeline to reconstruct a 3D personalized mannequin; and present a slice-based method for the symmetrization of the 3D mesh. </jats:sec

Study on 3D modeling and pattern-making for upper garment（上衣の三次元モデルの構築およびパターンメーキングに関する研究）

信州大学(Shinshu university)博士（工学）ThesisZHANG JUN. Study on 3D modeling and pattern-making for upper garment（上衣の三次元モデルの構築およびパターンメーキングに関する研究）. 信州大学, 2017, 博士論文. 博士（工学）, 甲第663号, 平成29年03月20日授与.doctoral thesi

Three-dimensional garment-size change modeled considering vertical proportions

ArticleINTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY. 29(1):84-95 (2017)journal articl

Fit evaluation of virtual garment try-on by learning from digital pressure data

Presently, garment fit evaluation mainly focuses on real try-on, and rarely deals with virtual try-on. With the rapid development of E-commerce, there is a profound growth of garment purchases through the internet. In this context, fit evaluation of virtual garment try-on is vital in the clothing industry. In this paper, we propose a Naive Bayes-based model to evaluate garment fit. The inputs of the proposed model are digital clothing pressures of different body parts, generated from a 3D garment CAD software; while the output is the predicted result of garment fit (fit or unfit). To construct and train the proposed model, data on digital clothing pressures and garment real fit was collected for input and output learning data respectively. By learning from these data, our proposed model can predict garment fit rapidly and automatically without any real try-on; therefore, it can be applied to remote garment fit evaluation in the context of e-shopping. Finally, the effectiveness of our proposed method was validated using a set of test samples. Test results showed that digital clothing pressure is a better index than ease allowance to evaluate garment fit, and machine learning-based garment fit evaluation methods have higher prediction accuracies

Upper garment 3D modeling for pattern making

Purpose - The purpose of this paper is to produce an upper garment model for three-dimensional (3D) pattern making. This model will take into account ease allowance and silhouette, and will be used to propose a size-changing method. Design/methodology/approach - The authors used two real garment bodices with a surface suitable for pattern development. The garments were fitted to a designated dummy body and scanned. Using the scanned data, the authors made those upper garment basic models suitable for 3D pattern making. Using one model, the authors produced two bodice patterns, one with the original seam lines and the other with seam lines that differed from the original ones, and then compared them with the original jacket bodice. To construct garment models that were different in size from the basic model, the authors calculated multiplication factors of cross-sectional dimensions (in the front, back and lateral directions) between the basic garment and the actual garment shape worn on a body for each basic model. Using the multiplication factors, the authors made two different size garment models from two different size dummies for each basic model. The authors used these models to make patterns and garments. Findings - The reproduced jackets had similar shapes, silhouettes and ease allowances to the original jacket. Two garments of different sizes for each original jacket were made using the multiplication factors, and these garments also had similar silhouettes to the original jacket. Research limitations/implications - The implications of the work could be the new size-changing method. Originality/value - Using the modeling method, the authors were able to make complex new garment models that take into account ease allowance and silhouette. The ability to size these models up or down using multiplication factors could be a substitute for the grading method.ArticleINTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY. 27(6):852-869 (2015)journal articl

Upper garment 3D modeling for pattern making

Purpose - The purpose of this paper is to produce an upper garment model for three-dimensional (3D) pattern making. This model will take into account ease allowance and silhouette, and will be used to propose a size-changing method. Design/methodology/approach - The authors used two real garment bodices with a surface suitable for pattern development. The garments were fitted to a designated dummy body and scanned. Using the scanned data, the authors made those upper garment basic models suitable for 3D pattern making. Using one model, the authors produced two bodice patterns, one with the original seam lines and the other with seam lines that differed from the original ones, and then compared them with the original jacket bodice. To construct garment models that were different in size from the basic model, the authors calculated multiplication factors of cross-sectional dimensions (in the front, back and lateral directions) between the basic garment and the actual garment shape worn on a body for each basic model. Using the multiplication factors, the authors made two different size garment models from two different size dummies for each basic model. The authors used these models to make patterns and garments. Findings - The reproduced jackets had similar shapes, silhouettes and ease allowances to the original jacket. Two garments of different sizes for each original jacket were made using the multiplication factors, and these garments also had similar silhouettes to the original jacket. Research limitations/implications - The implications of the work could be the new size-changing method. Originality/value - Using the modeling method, the authors were able to make complex new garment models that take into account ease allowance and silhouette. The ability to size these models up or down using multiplication factors could be a substitute for the grading method.ArticleINTERNATIONAL JOURNAL OF CLOTHING SCIENCE AND TECHNOLOGY. 27(6):852-869 (2015)journal articl

3D Garment Modelling - Creation of a Virtual Mannequin of the Human Body

This work presents the modelling and numerical simulation of mannequins as well as clothes in a 3D virtual environment. The paper explains garment modelling, with the objective of defining the development of a 3D body model that is useful and based on the demand of the garment industry. For this purpose a development strategy should be defined. Many scientists are working on the creative process for virtual garment development to create a garment directly on a 3D model of the human body, also called “ virtual tailoring”.The first strategic issue in this context that we present is that the model must necessarily incorporate the ease garment model associatively. These parameters define the priority concepts that are the draping and proper fit of the garment. The second point is that the transition between the 3D and 2D patterns, known as flattening 3D patterns, must be associative, precise and must take into account the real deformation of the fabric.Project entitled “Development of the research infrastructure of innovative techniques and technologies of the textile garment industry” CLO-2IN-TEX, financed by Operational Program Innovative Economy, 2007-2013, Action 2.

PERGAMO: Personalized 3D Garments from Monocular Video

Clothing plays a fundamental role in digital humans. Current approaches to animate 3D garments are mostly based on realistic physics simulation, however, they typically suffer from two main issues: high computational run-time cost, which hinders their development; and simulation-to-real gap, which impedes the synthesis of specific real-world cloth samples. To circumvent both issues we propose PERGAMO, a data-driven approach to learn a deformable model for 3D garments from monocular images. To this end, we first introduce a novel method to reconstruct the 3D geometry of garments from a single image, and use it to build a dataset of clothing from monocular videos. We use these 3D reconstructions to train a regression model that accurately predicts how the garment deforms as a function of the underlying body pose. We show that our method is capable of producing garment animations that match the real-world behaviour, and generalizes to unseen body motions extracted from motion capture dataset.Comment: Published at Computer Graphics Forum (Proc. of ACM/SIGGRAPH SCA), 2022. Project website http://mslab.es/projects/PERGAMO

Recognising the Clothing Categories from Free-Configuration Using Gaussian-Process-Based Interactive Perception

In this paper, we propose a Gaussian Process- based interactive perception approach for recognising highly- wrinkled clothes. We have integrated this recognition method within a clothes sorting pipeline for the pre-washing stage of an autonomous laundering process. Our approach differs from reported clothing manipulation approaches by allowing the robot to update its perception confidence via numerous interactions with the garments. The classifiers predominantly reported in clothing perception (e.g. SVM, Random Forest) studies do not provide true classification probabilities, due to their inherent structure. In contrast, probabilistic classifiers (of which the Gaussian Process is a popular example) are able to provide predictive probabilities. In our approach, we employ a multi-class Gaussian Process classification using the Laplace approximation for posterior inference and optimising hyper-parameters via marginal likelihood maximisation. Our experimental results show that our approach is able to recognise unknown garments from highly-occluded and wrinkled con- figurations and demonstrates a substantial improvement over non-interactive perception approaches