Ana Pierola

An ensemble of ordered logistic regression and random forest for child garment size matching

A fit assessment study of child garments is carried out.An original ensemble of ordered logistic regression and random forest for garment size assignment is proposed.Two new measures for understanding data with multivariate random forest are proposed.Promising results have been achieved with our methodology, especially if they are compared with the actual use of size charts. Size fitting is a significant problem for online garment shops. The return rates due to size misfit are very high. We propose an ensemble (with an original and novel definition of the weights) of ordered logistic regression and random forest (RF) for solving the size matching problem, where ordinal data should be classified. These two classifiers are good candidates for combined use due to their complementary characteristics. A multivariate response (an ordered factor and a numeric value assessing the fit) was considered with a conditional random forest. A fit assessment study was carried out with 113 children. They were measured using a 3D body scanner to obtain their anthropometric measurements. Children tested different garments of different sizes, and their fit was assessed by an expert. Promising results have been achieved with our methodology. Two new measures have been introduced based on RF with multivariate responses to gain a better understanding of the data. One of them is an intervention in prediction measure defined locally and globally. It is shown that it is a good alternative to variable importance measures and it can be used for new observations and with multivariate responses. The other proposed tool informs us about the typicality of a case and allows us to determine archetypical observations in each class.

3D-Based Resources Fostering the Analysis, Use, and Exploitation of Available Body Anthropometric Data

Today, there is an increasing availability of human body 3D data and an increasing number of anthropometric owners. This is due to the fact of the progressive conduction of large national surveys using high resolution 3D scanners and due to the increasing number of low-cost technologies for acquiring body shape with electronic consumer devices like webcams, smartphones or Kinect. However, the commercial use and exploitation in industry of digital anthropometric data is still limited to the use of 1D measurements extracted from this vast 3D information. There is a lack of universal resources enabling: to conjointly use and analyse datasets regardless from the source or type of scanning technology used, the flexible measurement extraction beyond pre-defined sets, and the analysis of the information contained in human shapes. This paper presents four software tool solutions aimed at addressing different user profiles and needs regarding the use and exploitation of the increasing number of 3D anthropometric data

Low-cost 3D foot scanner using a mobile app

The major finding of the present study was that the KS was improved around 10% with the use of IACS. No statistically significant difference was found in BV, PC, AS and IF. However, there was a trend that the AS and PC increased 9% and 5%, respectively. The significant increase of KS and a trend of increase of AS could possibly be explained by the foot arch and heel cup support which can provide evenly distributing pressure under the feet, maintaining alignment of the skeleton of lower extremity and further resulting in the KS and AS (Mulford et al., 2008). However, we found that the BV and PC were not statistically significant between IACS and FI. Although previous study indicated that one of the key factor of BV and PC was the ability to drive the body over a stabilized stride leg (Kageyama et al., 2014), this little improvement of BV and PC might be explained by the high level of the subjects in this study. Further study could include subjects of low level. Previous study indicated that the insole was one of the important factors for attenuating the IM (Chiu and Shiang, 2007). However, IM attenuation could be influenced by insole thickness or stiffness. Therefore, we suggested that thickness or stiffness of IACS was probably not enough to attenuate the IM. In conclusion, IACS provided KS and AS during baseball pitching.

Child t-shirt size data set from 3D body scanner anthropometric measurements and a questionnaire

A dataset of a fit assessment study in children is presented. Anthropometric measurements of 113 children were obtained using a 3D body scanner. Children tested a t-shirt of different sizes and a different model for boys and girls, and their fit was assessed by an expert. This expert labeled the fit as 0 (correct), −1 (if the garment was small for that child), or 1 (if the garment was large for that child) in an ordered factor called Size-fit. Moreover, the fit was numerically assessed from 1 (very poor fit) to 10 (perfect fit) in a variable called Expert evaluation. This data set contains the differences between the reference mannequin of the evaluated size and the child׳s anthropometric measurements for 27 variables. Besides these variables, in the data set, we can also find the gender, the size evaluated, and the size recommended by the expert, including if an intermediate, but nonexistent size between two consecutive sizes would have been the right size. In total, there are 232 observations. The analysis of these data can be found in Pierola et al. (2016) [2].

Data-driven three-dimensional reconstruction of human bodies using a mobile phone app

The advances and availability of technologies for the acquisition, registration and analysis of the three-dimensional (3D) shape of human bodies (or body parts) are resulting in the formation of large databases of parameterised meshes from which digital human body models can be derived. Such models can be used for the data-driven reconstruction of parameterised human body shapes from partial information such as one-dimensional (1D) measurements or 2D images. In this paper, we propose a new method for the reconstruction of 3D bodies from images gathered with a smartphone or tablet. Moreover, the method is implemented into a prototype app and tested at different levels through three experimental studies including synthetic models, 1:10 scale figurines and real children. The results demonstrate the feasibility of acquiring reliable anthropometric information easily at home by non-experts. This method and implementation have great potential for their application to the personalisation, size recommendation and virtual try-on simulation of wearable products.

Low-Cost Data-Driven 3D Reconstruction and its Applications

This paper describes two approaches for estimating human 3D shapes (i.e. full bodies or feet) using a regular smartphone or just entering a set of parameters (e.g. age, gender and self-taken measurements). The proposed approaches are based on data-driven 3D reconstructions, using parameterised shape spaces created from large 3D body or feet databases. The reconstruction algorithm finds the combination of shape parameters that best matches either the silhouettes extracted from the images or the body measurements entered. Despite not being actual body scanners, these solutions are easy-to-use and can provide enough accuracy for applications such as virtual try-on, made-to-measure or size allocation of certain types of wearables. Moreover, they can be distributed to the final consumer or to the points of sale at a really reduced cost (or even for free), thus overcoming the main barriers to the massive spreading of body scanners’ use to e-commerce, retail shops, new production pipelines or new business models. In order to illustrate these technologies, some examples of application to different contexts are provided, namely virtual worlds, e-commerce and personalisation.

3D Body Databases of the Spanish Population and its Application to the Apparel Industry

Since the year 2000, many anthropometric surveys have been conducted across the world using 3D body scanning technologies, most of them addressed to the apparel industry. This paper describes the application to the apparel industry of the 3D Spanish surveys (female, male and children) conducted from 2007 to 2015 by IBV gathering over 12.000 individual scans. It also presents tools that will help the apparel manufacturers and retailers to make an effective use of Spanish databases in the design as well as in the labelling of products addressed to the Spanish market and following the forthcoming size designation interval standards (EN 13402). These tools consist of a website providing with the basic anthropometric statistics, two books with the population measurements by age range (one for female and one for male populations), a collection of digital mannequins and a collection of physical mini-mannequins (scale 1/20). Moreover, the access to the 3D databases makes possible to IBV to extend the use of these data for the provision of new consultancy services for clothing companies about how to improve garment design and fitting.

Fast, Portable and Low-Cost 3D Foot Digitizers: Validity and Reliability of Measurements

This paper presents partial results of a larger validation study of two innovative products based on Data-driven 3D Reconstruction (D3DR) technology: a smartphone app, Avatar3D, and a portable booth, DomeScan. This study quantifies the reliability (Standard Error of Measurement, SEM, Intra-class Correlation Coefficient, ICC) of the automatic foot measurements elicited by these solutions and compares it to traditional anthropometry and to a commercial laser foot scanner. Moreover, it assesses the compatibility (systematic bias) of measurements among these techniques. The results show that, for the six measurements assessed, D3DR is as reliable as high resolution 3D scanners and more reliable than manual measurements made by an expert. Due to its lower cost, speed and portability they could be more suitable for retail and home environments than actual 3D scanners.

Kidsize: Always Get the Right Size

This paper describes the two innovations underpinning Kidsize concept and presents the results of their validation. The first one is a mobile phone app to measure a child in 3D by taking two pictures. This new method is more accurate and consistent than an untrained person using a measuring tape at home or in the shop. The second one is an expert system that recommends the size that best fits the child and assesses the fit of the garment at different body areas. Project results show that it can provide nearly 90% right size recommendations, thus outperforming existing methods like ageor height-based size guides, which achieve 40 and 60% right recommendations respectively.