AN EXPLORATORY STUDY ON MODERN 3D COMPUTERISED BODY SCANNING SYSTEM AND VARIOUS TYPES OF PATTERN MAKING SOFTWARE’S WITH THEIR CONSTRUCTIVE IMPLEMENTATION IN APPAREL INDUSTRY

Nowadays Computer-aided design (CAD) techniques such as Lectra Modaris is becoming exceedingly popular in the apparel industries worldwide for pattern construction because of its accuracy, efficiency and time-saving solutions to much arduous operation (Sayem et al., 2010). The principle objective of this article is to draft a set of pattern pieces by applying Lectra Modaris design environment after selecting a convenient style of trouser by different retail websites or fashion manuals. This paper contains all the essential draft patterns for the selected trouser such as front, back, waistband, pocket bag, pocket facing and fly piece which are constructed in Lectra Modaris V6R1 design software. These patterns are prepared after incorporating measurements into the design extracted from the body-scan point cloud data and from manual tape measurement. This paper also discussed briefly about the pattern construction procedure, different types of body scanning system and various types of pattern making software

AN EXPLORATORY STUDY ON MODERN 3D COMPUTERISED BODY SCANNING SYSTEM AND VARIOUS TYPES OF PATTERN MAKING SOFTWARE’S WITH THEIR CONSTRUCTIVE IMPLEMENTATION IN APPAREL INDUSTRY

Nowadays Computer-aided design (CAD) techniques such as Lectra Modaris is becoming exceedingly popular in the apparel industries worldwide for pattern construction because of its accuracy, efficiency and time-saving solutions to much arduous operation (Sayem et al., 2010). The principle objective of this article is to draft a set of pattern pieces by applying Lectra Modaris design environment after selecting a convenient style of trouser by different retail websites or fashion manuals. This paper contains all the essential draft patterns for the selected trouser such as front, back, waistband, pocket bag, pocket facing and fly piece which are constructed in Lectra Modaris V6R1 design software. These patterns are prepared after incorporating measurements into the design extracted from the body-scan point cloud data and from manual tape measurement. This paper also discussed briefly about the pattern construction procedure, different types of body scanning system and various types of pattern making software

Manufacturing processes in the textile industry. Expert Systems for fabrics production

 The textile industry is characterized by the economic activity whose objective is the production of fibres, yarns, fabrics, clothing and textile goods for home and decoration, as well as technical and industrial purposes. Within manufacturing, the Textile is one of the oldest and most complex sectors which includes a large number of sub-sectors covering the entire production cycle, from raw materials and intermediate products, to the production of final products. Textile industry activities present different subdivisions,each with its own traits. The length of the textile process and the variety of its technicalprocesses lead to the coexistence of different sub-sectors in regards to their business structure and integration. The textile industry is developing expert systems applicationsto increase production, improve quality and reduce costs. The analysis of textile designs or structures includes the use of mathematical models to simulate the behavior of the textile structures (yarns, fabrics and knitting). The Finite Element Method (FEM) has largely facilitated the prediction of the behavior of that textile structure under mechanical loads. For classification problems Artificial Neural Networks (ANNs) have proved to be a very effective tool as a quick and accurate solution. The Case-Based Reasoning (CBR) method proposed in this study complements the results of the finite element simulation, mathematical modeling and neural networks methods

Advances in Virtual Prototyping: Opportunities for Clothing Manufacturers

This paper summarises the recent developments in 3D clothing design systems and discusses the features of available CAD systems. It also highlights the benefits of using such systems that the clothing manufacturers can enjoy

Three-dimensional simulation of warp knitted structures based on geometric unit cell of loop yarns

Warp knitted fabrics are typically three-dimensional (3D) structures, and their design is strongly dependent on the structural simulation. Most of existing simulation methods are only capable of two-dimensional (2D) modeling, which lacks perceptual realism and cannot show design defects, making it hard for manufacturers to produce the required fabrics. The few existing methods capable of 3D structural simulation are computationally demanding and therefore can only run on powerful computers, which makes it hard to utilize online platforms (e.g. clouds, mobile devices, etc.) for simulation and design communication. To fill the gap, a novel, lightweight and agile geometric representation of warp knitting loops is proposed to establish a new framework of 3D simulation of complex warp knitted structures. Further, the new representation has great simplicity, flexibility and versatility and is used to build high-level models in representing the 3D structures of warp knitted fabrics with complex topologies. Simulations of a variety of warp knitted fabrics are presented to demonstrate the capacity and generalizability of this newly proposed methodology. It has also been used in virtual design of warp knitted fabrics in wireless mobile devices for digital manufacture and provides a functional reference model based on this simplified unit cell of warp knitted loops to simulate more realistic 3D warp knitted fabrics

3D CAD systems for the clothing industry

The approaches for designing virtual garments may be categorised as ‘2D to 3D’ and ‘3D to 2D’. The former refers to draping flat digital pattern pieces on a virtual mannequin, and the later indicates the development of clothing design on a realistic body and subsequent flattening into 2D pattern pieces. Several computer-aided design (CAD) systems for garment visualisation in space from flat patterns have already been introduced into the clothing industry. Any industrial application of the pattern flattening technique is yet to be made, due to the non-availability of an appropriate CAD system on the market. This article reviews the historical developments of 3D CAD systems for the clothing industry, and assesses the features of currently available systems on market

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

An investigation on the framework of dressing virtual humans

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Realistic human models are widely used in variety of applications. Much research has been carried out on improving realism of virtual humans from various aspects, such as body shapes, hair, and facial expressions and so on. In most occasions, these virtual humans need to wear garments. However, it is time-consuming and tedious to dress a human model using current software packages [Maya2004]. Several methods for dressing virtual humans have been proposed recently [Bourguignon2001, Turquin2004, Turquin2007 and Wang2003B]. The method proposed by Bourguignon et al [Bourguignon2001] can only generate 3D garment contour instead of 3D surface. The method presented by Turquin et al. [Turquin2004, Turquin2007] could generate various kinds of garments from sketches but their garments followed the shape of the body and the side of a garment looked not convincing because of using simple linear interpolation. The method proposed by Wang et al. [Wang2003B] lacked interactivity from users, so users had very limited control on the garment shape.This thesis proposes a framework for dressing virtual humans to obtain convincing dressing results, which overcomes problems existing in previous papers mentioned above by using nonlinear interpolation, level set-based shape modification, feature constraints and so on. Human models used in this thesis are reconstructed from real human body data obtained using a body scanning system. Semantic information is then extracted from human models to assist in generation of 3 dimensional (3D) garments. The proposed framework allows users to dress virtual humans using garment patterns and sketches. The proposed dressing method is based on semantic virtual humans. A semantic human model is a human body with semantic information represented by certain of structure and body features. The semantic human body is reconstructed from body scanned data from a real human body. After segmenting the human model into six parts some key features are extracted. These key features are used as constraints for garment construction.Simple 3D garment patterns are generated using the techniques of sweep and offset. To dress a virtual human, users just choose a garment pattern, which is put on the human body at the default position with a default size automatically. Users are allowed to change simple parameters to specify some sizes of a garment by sketching the desired position on the human body.To enable users to dress virtual humans by their own design styles in an intuitive way, this thesis proposes an approach for garment generation from user-drawn sketches. Users can directly draw sketches around reconstructed human bodies and then generates 3D garments based on user-drawn strokes. Some techniques for generating 3D garments and dressing virtual humans are proposed. The specific focus of the research lies in generation of 3D geometric garments, garment shape modification, local shape modification, garment surface processing and decoration creation. A sketch-based interface has been developed allowing users to draw garment contour representing the front-view shape of a garment, and the system can generate a 3D geometric garment surface accordingly. To improve realism of a garment surface, this thesis presents three methods as follows. Firstly, the procedure of garment vertices generation takes key body features as constraints. Secondly, an optimisation algorithm is carried out after generation of garment vertices to optimise positions of garment vertices. Finally, some mesh processing schemes are applied to further process the garment surface. Then, an elaborate 3D geometric garment surface can be obtained through this series of processing. Finally, this thesis proposes some modification and editing methods. The user-drawn sketches are processed into spline curves, which allow users to modify the existing garment shape by dragging the control points into desired positions. This makes it easy for users to obtain a more satisfactory garment shape compared with the existing one. Three decoration tools including a 3D pen, a brush and an embroidery tool, are provided letting users decorate the garment surface by adding some small 3D details such as brand names, symbols and so on. The prototype of the framework is developed using Microsoft Visual Studio C++,OpenGL and GPU programming

Sensing Highly Non-Rigid Objects with RGBD Sensors for Robotic Systems

The goal of this research is to enable a robotic system to manipulate clothing and other highly non-rigid objects using an RGBD sensor. The focus of this thesis is to define and test various algorithms / models that are used to solve parts of the laundry process (i.e. handling, classifying, sorting, unfolding, and folding). First, a system is presented for automatically extracting and classifying items in a pile of laundry. Using only visual sensors, the robot identifies and extracts items sequentially from the pile. When an item is removed and isolated, a model is captured of the shape and appearance of the object, which is then compared against a dataset of known items. The contributions of this part of the laundry process are a novel method for extracting articles of clothing from a pile of laundry, a novel method of classifying clothing using interactive perception, and a multi-layer approach termed L-M-H, more specifically L-C-S-H for clothing classification. This thesis describes two different approaches to classify clothing into categories. The first approach relies upon silhouettes, edges, and other low-level image measurements of the articles of clothing. Experiments from the first approach demonstrate the ability of the system to efficiently classify and label into one of six categories (pants, shorts, short-sleeve shirt, long-sleeve shirt, socks, or underwear). These results show that, on average, classification rates using robot interaction are 59% higher than those that do not use interaction. The second approach relies upon color, texture, shape, and edge information from 2D and 3D data within a local and global perspective. The multi-layer approach compartmentalizes the problem into a high (H) layer, multiple mid-level (characteristics(C), selection masks(S)) layers, and a low (L) layer. This approach produces \u27local\u27 solutions to solve the global classification problem. Experiments demonstrate the ability of the system to efficiently classify each article of clothing into one of seven categories (pants, shorts, shirts, socks, dresses, cloths, or jackets). The results presented in this paper show that, on average, the classification rates improve by +27.47% for three categories, +17.90% for four categories, and +10.35% for seven categories over the baseline system, using support vector machines. Second, an algorithm is presented for automatically unfolding a piece of clothing. A piece of cloth is pulled in different directions at various points of the cloth in order to flatten the cloth. The features of the cloth are extracted and calculated to determine a valid location and orientation in which to interact with it. The features include the peak region, corner locations, and continuity / discontinuity of the cloth. In this thesis, a two-stage algorithm is presented, introducing a novel solution to the unfolding / flattening problem using interactive perception. Simulations using 3D simulation software, and experiments with robot hardware demonstrate the ability of the algorithm to flatten pieces of laundry using different starting configurations. These results show that, at most, the algorithm flattens out a piece of cloth from 11.1% to 95.6% of the canonical configuration. Third, an energy minimization algorithm is presented that is designed to estimate the configuration of a deformable object. This approach utilizes an RGBD image to calculate feature correspondence (using SURF features), depth values, and boundary locations. Input from a Kinect sensor is used to segment the deformable surface from the background using an alpha-beta swap algorithm. Using this segmentation, the system creates an initial mesh model without prior information of the surface geometry, and it reinitializes the configuration of the mesh model after a loss of input data. This approach is able to handle in-plane rotation, out-of-plane rotation, and varying changes in translation and scale. Results display the proposed algorithm over a dataset consisting of seven shirts, two pairs of shorts, two posters, and a pair of pants. The current approach is compared using a simulated shirt model in order to calculate the mean square error of the distance from the vertices on the mesh model to the ground truth, provided by the simulation model

The application of three-dimensional mass-spring structures in the real-time simulation of sheet materials for computer generated imagery

Despite the resources devoted to computer graphics technology over the last 40 years, there is still a need to increase the realism with which flexible materials are simulated. However, to date reported methods are restricted in their application by their use of two-dimensional structures and implicit integration methods that lend themselves to modelling cloth-like sheets but not stiffer, thicker materials in which bending moments play a significant role. This thesis presents a real-time, computationally efficient environment for simulations of sheet materials. The approach described differs from other techniques principally through its novel use of multilayer sheet structures. In addition to more accurately modelling bending moment effects, it also allows the effects of increased temperature within the environment to be simulated. Limitations of this approach include the increased difficulties of calibrating a realistic and stable simulation compared to implicit based methods. A series of experiments are conducted to establish the effectiveness of the technique, evaluating the suitability of different integration methods, sheet structures, and simulation parameters, before conducting a Human Computer Interaction (HCI) based evaluation to establish the effectiveness with which the technique can produce credible simulations. These results are also compared against a system that utilises an established method for sheet simulation and a hybrid solution that combines the use of 3D (i.e. multilayer) lattice structures with the recognised sheet simulation approach. The results suggest that the use of a three-dimensional structure does provide a level of enhanced realism when simulating stiff laminar materials although the best overall results were achieved through the use of the hybrid model