The System of Selection and Sale of Ready-to-Wear Clothes in a Virtual Environment

Petrosova, I. A.; Andreeva, E. G.; Гусева, М. А.

doi:10.1109/eastconf.2019.8725390

Cited by 7 publications

(4 citation statements)

References 6 publications

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“…Early scanners were used for a custom fit, automated size selection, dress form manufacture, and anthropometric studies (Istook & Hwang, 2001;Daanen & Psikuta, 2018;Petrosova et al, 2019). 3D body scanners principally used white light or lasers for their light sources.…”

Section: D Body Scannersmentioning

confidence: 99%

“…The beginning of 3D technology is attributed to Douty (1968), who first used somatometry as a technology where the three-dimensional surface of the body was captured by photography from a camera. This was followed by other events like the first 3D body scanning system known as the Loughborough anthropometric shadow scanner (LASS) and the first used in anthropometry and ergonomics fields (Douty, 1968;Sohn, 2012;Bagarello, 2016;Daanen & Psikuta, 2018;Petrosova et al, 2019).…”

Section: D Body Scannersmentioning

confidence: 99%

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Digital Innovation for Sustainable Fashion: Virtual Fitting Rooms as a Strategy to Minimize Waste and E-commerce Returns

Vitola

2024

Preprint

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<p>This study aims to determine the efficacy of digital innovations and Virtual Fitting Rooms (VFRs) in minimizing online returns and waste in the fashion industry. This study used both primary and secondary data, including 1) a narrative literature review approach based on data from multiple secondary sources, including scientific journals, e-commerce reports, tech company websites, and other relevant and verified sources, 2) an online survey with sixteen respondents and eight semi-structured interviews with tech companies and virtual fitting rooms developers were conducted to establish baseline data of their perception on the role of developers and VFR tech companies concerning sustainable fashion and reverse logistics. This study assessed information of current VFR apps, including issues with technology development, relationships with e-commerce retailers, effect of VFR in reducing online returns and increasing customer satisfaction. Collected data determined the effects of existing VFRs and digital solutions adopted by the fashion industry to help customers in the sizing and fitting process to reduce online returns and e-commerce waste.</p> <p>The results highlight that VFRs are effective in minimizing returns, increasing customer satisfaction, and promoting sustainability by reducing CO2 emissions due to transportation. This study shows that VFRs could reduce 31.3% of reverse logistic costs and minimize store sizing sampling. There is room for future research on the usage of VFR in 3D cloth simulation engines in pre-production and designers’ collections, which could potentially have a more significant environmental impact on the minimization of fashion waste and overproduction.</p>

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Section: D Body Scannersmentioning

confidence: 99%

Section: D Body Scannersmentioning

confidence: 99%

Digital Innovation for Sustainable Fashion: Virtual Fitting Rooms as a Strategy to Minimize Waste and E-commerce Returns

Vitola

2024

Preprint

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“…Indeed, some authors have set up a dataset of more than one hundred thousand images labeled with brands, types, colors, materials, and prices so that customers can choose the right clothes when shopping online (4-7). Additionally, many businesses have seen the strong influence of the Internet potential on consumers, which leads them to create a lot of online shopping websites such as research (8)(9)(10)(11)(12). On such websites, customers will choose sizes and try on clothes through a virtual simulation program which helps them fit clothes in a short time.…”

Section: Introductionmentioning

confidence: 99%

The simulation modeling to choose styles of torso dresses byfuzzy logic

Nguyen

2023

BIJSCIT

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This study presents the use of the fuzzy logic technique in choosing Torso dresses for online shopping. Dressstyles are established based on analyzing three factors that prioritize clothing selection using the Pareto chart.These factors include the dress’s form, thickness, and color fabric of the dress. These are the three inputvariables of this model, and each of them has different membership functions. The first input variable is theform of the modeling, and has two membership functions. The second is the fabric type that can be used fordresses, and has five membership functions. The third input variable is the color of the fabric, and has threemembership functions. The output is a type of outfit looked for so the actual survey method is conducted inthe customers-interest-scale of clothing. The fuzzy If-Then rule and Sugeno controller are used in this modeling.There are 30 Torso dress styles coded for application to fuzzy logic modeling. Besides, the theoretical methodis applied in a 2D flat pattern designing a basic Torso pattern and a fuzzy logic model. Additionally, albumsof dress styles are created by the 3D simulation method as well as the model’s feasibility is evaluated by theexpert method.

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“…Anthropometrics is the study of measurements of the human body taken from diverse populations such as age, gender or nationality. Applications of using the anthropometric consist of a suitable design of clothing [22] and workstation [23] from this human body reference. Anthropometric data involves human body measurements such as weight, height, and length.…”

Section: Introductionmentioning

confidence: 99%

Anthropometric Ratios for Lower-Body Detection Based on Deep Learning and Traditional Methods

2022

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Lower-body detection can be useful in many applications, such as the detection of falling and injuries during exercises. However, it can be challenging to detect the lower-body, especially under various lighting and occlusion conditions. This paper presents a novel lower-body detection framework using proposed anthropometric ratios and compares the performance of deep learning (convolutional neural networks and OpenPose) and traditional detection methods. According to the results, the proposed framework helps to successfully detect the accurate boundaries of the lower-body under various illumination and occlusion conditions for lower-limb monitoring. The proposed framework of anthropometric ratios combined with convolutional neural networks (A-CNNs) also achieves high accuracy (90.14%), while the combination of anthropometric ratios and traditional techniques (A-Traditional) for lower-body detection shows satisfactory performance with an averaged accuracy (74.81%). Although the accuracy of OpenPose (95.82%) is higher than the A-CNNs for lower-body detection, the A-CNNs provides lower complexity than the OpenPose, which is advantageous for lower-body detection and implementation on monitoring systems.

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The System of Selection and Sale of Ready-to-Wear Clothes in a Virtual Environment

Cited by 7 publications

References 6 publications

Digital Innovation for Sustainable Fashion: Virtual Fitting Rooms as a Strategy to Minimize Waste and E-commerce Returns

Digital Innovation for Sustainable Fashion: Virtual Fitting Rooms as a Strategy to Minimize Waste and E-commerce Returns

The simulation modeling to choose styles of torso dresses byfuzzy logic

Anthropometric Ratios for Lower-Body Detection Based on Deep Learning and Traditional Methods

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