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The circular design process in contemporary fashion design, from two-dimensional (2D) sketching and pattern making to three-dimensional (3D) prototypes, can be facilitated by virtual prototyping. Virtual pressure representations on avatars provide visual and quantitative information regarding garment fit and comfort, which are particularly important for active wear. The purpose of this study is to investigate the benefits of using avatars in active poses from 3D body scans and the use of digital 3D tools for the design process and the prediction of fit of active wear.

This research initially explores virtual fit of cycling wear in active poses and compares the actual pressure values from humans with virtual pressure maps on custom avatars made from body scans in cycling poses across a range of sizes.

Similar fit results were achieved visually in both the standing and cycling poses. However, the comparisons showed no correlation between the actual and virtual pressure data. Of the 32 cases representing different combinations of the parameters of this research (four sizes, two garment types, four active poses), the differences were significant. The results suggest that, rather than providing a direct correlation with pressure values on the body, the main value of avatar data is in providing comparative visual support for fit evaluation.

The approach taken in this research, which considers the active pose and the size range, potentially contributes to the improvement of virtual fit technology, and its more effective use in apparel product development and fit evaluation.

The design and testing of clothing for activewear requires complex assessments of the suitability of the clothing when the body is in motion. The purpose of this paper is to investigate full body 3D scanning of active body poses in order to develop “watertight” digital models and half-scale dress forms to facilitate design, pattern making and fit analyses. Issues around creating a size set of scans in order to facilitate fit testing of activewear across a size range were also explored.

Researchers experimented to discover effective methods for 3D body capture in the cycling position and reconstruction of the body in a reliable way. In total, 25 cyclists were scanned and size representatives were selected from these participants. Methods of creating half-scale forms were developed that make optimum use of modern materials and technologies. Half-scale dress forms were created in two active positions in a range of sizes for fit testing and design. A set of half-scale and full-scale bike shorts in two styles were manufactured and fit tested on the half-scale forms compared to fit testing on the scan participants to test validity of this method of assessing fit.

Issues in capturing and reconstructing areas occluded in the scanning process, and reconstructing the interface with the bicycle seat were addressed. Active digital forms were developed across the size range, from which both digital avatars and physical mannequins were developed for pattern development and fit testing. The production and use of precisely half-scaled tools for garment testing was achieved and validated by comparing fit test results in active positions on the half-scale forms and on participants who were scanned to create these forms.

Design modifications for active positions to date are based on linear measurements alone, which do not define the 3D body adequately. Despite much research using body scanners, only limited data exist on the body in active poses, and the concept of creating half-scale forms by scanning fit models throughout the size range in active body positions is a novel concept. The progress made in resolving material and process experiments in creating the actual half-scale forms, and testing their suitability for fit testing provides a basis for further research aimed at developing similar dress forms for other activewear garments.

The purpose of this paper is to identify common issues among commercial body size charts, and to propose a sizing improvement methodology without changing the number of sizes in the range. One goal is to equalize the number of people accommodated by each size within the range, and to propose a way to evaluate the effectiveness of the improvement.

The proposed method consists of three phases: (Phase I) identify target population; (Phase II) analysis of existing size charts; and (Phase III) improvement of the initial size chart. Phase III is the key process, which includes repeated manipulation of intersize intervals of the three primary measurements (chest, waist and hip) for improved consistency of overall and interior accommodate rates among the three measurement categories. A program was developed in RStudio® to generate trials and side-by-side bar plots for visualization of the differences in accommodate rates.

The main issue in commercial body size charts observed is the inconsistency of the interior accommodation rates among measurement categories. Some other issues include: lack of important measurements, failure to provide ranges and gaps between measurement ranges of adjacent sizes.

This paper proposed a complete work flow to improve body size charts to fix the common issues. The method integrates historic size information and new anthropometric information extracted from a national-scale sizing database (e.g. SizeUSA). The study also brought association of the secondary body measurements with primary measurements without using linear regression. Hence, information from body size charts can be more efficiently used in acquiring other size information.

The purpose of this paper is to develop an intelligent system for fashion style selection for non-standard female body shapes.

With the goal of creating natural aesthetic relationship between the body shape and the shape of clothing, garments designed for the upper and lower body are combined to fit different female body shapes, which are classified as V, A, H and O-shapes. The proposed intelligent system combines genetic algorithm (GA) with a neural network classifier, which is trained using the particle swarm optimization (PSO). The former, called genetic search, is used to find the optimal design parameters corresponding to a best fit for the desired target, while the task of the latter, called neural classification, is to evaluate fitness (goodness) of each evolved new fashion style.

The experimental results are fashion styling recommendations for the four female body shapes, drawn from 260 possible combinations, based on variations from 15 attributes. These results are considered to be a strong indication of the potential benefits of the application of intelligent systems to fashion styling.

The proposed intelligent system combines the effective searching capabilities of two approaches. The first approach uses the GA for identifying best fits to the target shape of the body in the solution space. The second is the PSO for finding optimal (with respect to training mean-squared error) weight and threshold parameters of the neural classifier, which is able to evaluate the fitness of successively evolved fashion styles.

Identification of human body shapes has been a key issue to develop sizing standards for ready‐to‐wear and to develop made‐to‐measure applications. Current methods to identify the body shapes are mostly based on subjective/visual determination approaches. The purpose of this paper is to look for numerical evaluation parameters for an objective method in order to classify the body shapes and to build up an automated process link.

Female subjects were chosen for the experimental design. 3D body scanning technology was integrated in the process for measurement taking and body silhouette detection of the sample group. Based on this sample data set, body shape identification was realized by referees as visual analyses, and additionally, an objective method was tried out by using body dimensions as numerical evaluation parameters. Obtained results with the sample group were inserted in a database and a body shape calculation tool was developed.

Statistical analyses showed that there is mostly a good agreement between the pairs of the evaluations including the objective calculation methods and the subjective assessments of the referees. The calculation tool was designed as web‐based software in order to integrate with further developments and automation purposes.

A new automatic tool was developed to make the body shape classification objective and repeatable. By integrating this tool to the product development chain, a continuous process link can be provided for the companies through the way for better fitting clothing.