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1 – 10 of over 14000
Article
Publication date: 31 May 2013

Qijin Chen, Jituo Li, Zheng Liu, Guodong Lu, Xinyu Bi and Bei Wang

Clothing retrieval is very useful to help the clients to efficiently search out the apparel they want. Currently, the mainstream clothing retrieval methods are attribute…

Abstract

Purpose

Clothing retrieval is very useful to help the clients to efficiently search out the apparel they want. Currently, the mainstream clothing retrieval methods are attribute semantics based, which however are inconvenient for common clients. The purpose of this paper is to provide an easy‐to‐operate apparels retrieval mode with the authors' novel approach of clothing image similarity measurement.

Design/methodology/approach

The authors measure the similarity between two clothing images by computing the weighted similarities between their bundled features. Each bundled feature consists of the point features (SIFT) which are further quantified into local visual words in a maximally stable extremal region (MSER). The authors weight the importance of bundled features by the precision of SIFT quantification and local word frequency that reflects the frequency of the common visual words appeared in two bundled features. The bundled features similarity is computed from two aspects: local word frequency; and SIFTs distance matrix that records the distances between every two SIFTs in a bundled feature.

Findings

Local word frequencies improves the recognition between two bundled features with the same common visual words but different local word frequency. SIFTs distance matrix has the merits of scale invariance and rotation invariance. Experimental results show that this approach works well in the situations with large clothing deformation, background exchange and part hidden, etc. And the similarity measurement of Weight+Bundled+LWF+SDM is the best.

Originality/value

This paper presents an apparel retrieval mode based on local visual features, and presents a new algorithm for bundled feature matching and apparel similarity measurement.

Details

International Journal of Clothing Science and Technology, vol. 25 no. 2
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 10 February 2021

Niromi Seram, Rivini Mataraarachchi and Thanuri Jayaneththi

Exercising is a key approach adopted by muscular dystrophy patients to halt the weakening of muscles as it can eventually lead to serious immobility issues. Though it is…

Abstract

Purpose

Exercising is a key approach adopted by muscular dystrophy patients to halt the weakening of muscles as it can eventually lead to serious immobility issues. Though it is essential to exercise on a daily basis for healthy living, there is no mention of any research effort in the current literature regarding the development of an apparel product for these mobility-affected patients that might assist them both in meeting their exercising needs and providing them some comfort in their daily living. Thus, this paper aims to focus on identifying the specific needs of muscular dystrophy victims and proposing special adaptive clothing solutions to support their daily exercise and mobility needs.

Design/methodology/approach

To achieve the objectives of this study, attention was focused on the muscular dystrophy afflicted women in Sri Lanka. Semi-structured interviews were conducted with the female victims of muscular dystrophy and their lifestyles were observed carefully; additional data were gathered by holding semi-structured interviews with their physiotherapists. Further, interviews were conducted with both garment technologists and fabric technologists too. Data gathered through these methods were analyzed qualitatively using the principles of thematic analysis and then aggregate conclusions were drawn.

Findings

It was observed that the patients were engaged in special activities such as exercising three times a day besides following their normal day-to-day activities to maintain and develop muscle strength. It soon became evident that these women found it difficult to perform their daily exercise routines with their regular clothing and were looking for custom made clothing they could wear all day long in comfort and avoid the problems that arose while exercising. The study specifies the requirements that must be met to satisfy both generic and specific needs. Considering all these aspects some adaptive clothing solutions were proposed to support daily exercising activity with respect to comfort, convenience, health and safety, as well as socio-cultural and psychological needs.

Originality/value

The area of fusing generic and specific features to support the daily exercising needs of muscular dystrophy victims is an untouched field of experimentation and being a need of the disabled, the present study marks a milestone on the way to a novel area of apparel design, besides exploring a new field of research.

Details

Research Journal of Textile and Apparel, vol. 25 no. 2
Type: Research Article
ISSN: 1560-6074

Keywords

Article
Publication date: 2 July 2020

Xiaoxi Zhou, Jianfei Meng, Guosheng Wang and Qin Xiaoxuan

This paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing

Abstract

Purpose

This paper examines the problem of lack of historical data and inadequate consideration of factors influencing demand in the forecasting of demand for fast fashion clothing and proposes an improved Bass model for the forecasting of such a demand and the demand for new clothing products.

Design/methodology/approach

From the perspective of how to solve the lack of data and improve the precision of the clothing demand forecast, this paper studies the measurement of clothing similarity and the addition of demand impact factors. Using the fuzzy clustering–rough set method, the degree of resemblance of clothing is determined, which provides a basis for the scientific utilisation of historical data of similar clothing to forecast the demand for new clothing. Besides, combining the influence of consumer preferences and seasonality on demand forecasting, an improved Bass model for a fast fashion clothing demand forecast is proposed. Finally, with a forecasting example of demand for clothing, this study also tests the validity of the method.

Findings

The objective measurement method of clothing similarity in this paper solves the problem of the difficult forecasting of demand for fast fashion clothing due to a lack of sales data at the preliminary stage of the clothing launch. The improved Bass model combines, comprehensively, consumer preferences and seasonality and enhances the forecast precision of demand for fast fashion clothing.

Originality/value

The paper puts forward a scientific, quantitative method for the forecasting of new clothing products using historical sales data of similar clothing, thus solving the problem of lack of sales data of the fashion.

Details

International Journal of Clothing Science and Technology, vol. 33 no. 1
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 27 August 2020

Xiaohong Mo, Enle Sun and Xian Yang

The purpose of this paper is to study online clothing consumers' behaviour and their visual attention mechanism to provide objective and quantitative evidences for the…

Abstract

Purpose

The purpose of this paper is to study online clothing consumers' behaviour and their visual attention mechanism to provide objective and quantitative evidences for the display and sales of online clothing.

Design/methodology/approach

Firstly, this paper conducted a Focus Group Methodology and questionnaire survey to obtain concern factors of online clothing. Secondly, the online clothing's bottom-up visual stimulation and consumer's top-down expectations were analysed, and proposed the hypotheses about significant stimulus of clothing and consumer's emotional experience. Thirdly, the online clothing consumer's visual attention rules and related qualitative results were discussed, and proposed visual attention law for online clothing. Finally, took the company's 84th quarter clothing design practices as research projects, all the hypotheses were demonstrated through eye movement physiology experiments, online clothing trial release and node sales data.

Findings

Online clothing has unique visual display ways compared with other online products such as online advertising, brands and food packaging. Clothing patterns of unfamiliar (fresh) font shapes are more attractive than the patterns of familiar fonts. The cause of the bottom-up visual attention bias is the contrast between clothing features, not the absolute stimulus intensity of the features themselves. Clothing factors can change their emotional experience from no difference to significant difference under the influence of other clothing factors.

Originality/value

Put forward hypotheses of online clothing consumer behaviour and its visual attention mechanism, provided objective and quantitative evidences through eye tracker.

Details

International Journal of Clothing Science and Technology, vol. 33 no. 3
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 25 February 2022

Jun Xiang, Ruru Pan and Weidong Gao

The paper aims to propose a novel method based on deep sparse convolutional neural network (CNN) for clothing recognition. A CNN based on inception module is applied to…

Abstract

Purpose

The paper aims to propose a novel method based on deep sparse convolutional neural network (CNN) for clothing recognition. A CNN based on inception module is applied to bridge pixel-level features and high-level category labels. In order to improve the robustness accuracy of the network, six transformation methods are used to preprocess images. To avoid representational bottlenecks, small-sized convolution kernels are adopted in the network. This method first pretrains the network on ImageNet and then fine-tune the model in clothing data set.

Design/methodology/approach

The paper opts for an exploratory study by using the control variable comparison method. To verify the rationality of the network structure, lateral contrast experiments with common network structures such as VGG, GoogLeNet and AlexNet, and longitudinal contrast tests with different structures from one another are performed on the created clothing image data sets. The indicators of comparison include accuracy, average recall, average precise and F-1 score.

Findings

Compared with common methods, the experimental results show that the proposed network has better performance on clothing recognition. It is also can be found that larger input size can effectively improve accuracy. By analyzing the output structure of the model, the model learns a certain “rules” of human recognition clothing.

Originality/value

Clothing analysis and recognition is a meaningful issue, due to its potential values in many areas, including fashion design, e-commerce and retrieval system. Meanwhile, it is challenging because of the diversity of clothing appearance and background. Thus, this paper raises a network based on deep sparse CNN to realize clothing recognition.

Details

International Journal of Clothing Science and Technology, vol. 34 no. 1
Type: Research Article
ISSN: 0955-6222

Keywords

Open Access
Article
Publication date: 25 May 2021

Maarit Aakko and Kirsi Niinimäki

Extending the active lifetimes of garments by producing better quality is a widely discussed strategy for reducing environmental impacts of the garment industry. While…

4409

Abstract

Purpose

Extending the active lifetimes of garments by producing better quality is a widely discussed strategy for reducing environmental impacts of the garment industry. While quality is an important aspect of clothing, the concept of quality is ambiguous, and, moreover, consumers may perceive quality in individual ways. Therefore, it is important to deepen the general understanding regarding the quality of clothing.

Design/methodology/approach

This paper presents an integrated literature review of the recent discussion of perceived quality of clothing and of the links between quality and clothing lifetimes; 47 selected articles and other literature obtained primarily through fashion/clothing/apparel journals were included in this review.

Findings

The main ideas from the articles are thematized into the following sections: the process of assessment, levels involved in assessment, multidimensional cues of assessment, and quality and clothing use times. The paper highlights that perceiving quality is a process guided by both expectations and experience, and assembles the various aspects into a conceptual map that depicts the connections between the conceptual levels involved in assessing quality. It also illustrates connections between quality and clothing use times.

Research limitations/implications

This paper focused on perceived quality on a conceptual level. Further studies could examine and establish deeper links between quality, sustainability and garment lifespans.

Originality/value

The study draws together studies on perceived quality, presenting the foundational literature and key concepts of quality of clothing. It summarizes them in a conceptual map that may help visualize various aspects affecting the assessment of quality and deepen the general understanding of the quality of garments.

Details

Journal of Fashion Marketing and Management: An International Journal, vol. 26 no. 1
Type: Research Article
ISSN: 1361-2026

Keywords

Article
Publication date: 24 December 2021

Xiaoxi Zhou, Yue Xu and Tui Chen

This paper aims to identify the relationship between users' perception image, clothing design features and users' preference and propose a clothing design scheme based on…

Abstract

Purpose

This paper aims to identify the relationship between users' perception image, clothing design features and users' preference and propose a clothing design scheme based on users perception image and users' preference.

Design/methodology/approach

In this paper, men's suit is composed into multiple design features under the design elements. Using the orthogonal experiment method, 16 schemes of the representative suit are designed. Through perception evaluation experiment, users' perception images and preference degree of the samples are obtained. By partial least squares (PLS) analysis method, the models between users' perception image, suit design features and users' preference are built.

Findings

The interrelationship between the three is identified by establishing PLS models between users' perception image, suit design features and users' preference. According to the coefficients of the models, the optimization schemes of men's suits considering users' perception image and preference are proposed. Verification results show that the optimization schemes are significantly better than other schemes.

Originality/value

The results of this paper can be used for consumer demand-oriented clothing design and provide references and methods for converting consumer's perceived needs into clothing design features.

Details

International Journal of Clothing Science and Technology, vol. 34 no. 3
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 3 February 2022

Matthew A. Lapierre, Anjali Ashtaputre and Jennifer Stevens Aubrey

Using gender schema theory, this study aims to explore how children’s graphic t-shirts from clothing retailers in the USA differed on gendered themes for graphic t-shirts…

Abstract

Purpose

Using gender schema theory, this study aims to explore how children’s graphic t-shirts from clothing retailers in the USA differed on gendered themes for graphic t-shirts targeting boys or girls, in addition to differences for shirts that were higher in cost.

Design/methodology/approach

This content analysis of children’s t-shirts included 866 child-targeted shirts taken from the online retail portals from 11 clothing retailers in the USA. Shirts were coded for gendered themes on the front torso part of the shirt and included traditional boy themes (e.g. aggression, instrumentality) and girl themes (e.g. compassion, passivity). In addition, the retail prices for each shirt were recorded at the time of data collection.

Findings

The results demonstrated that children’s graphic t-shirts starkly differentiate between femininity and masculinity based on their target. Boys’ shirts were significantly more likely to feature active themes, whereas girls’ shirts were more likely to focus on social belonging and interpersonal connection. Boys’ shirts were also more likely to display themes linked to dominance/aggression but not compassion. Girls’ shirts were more likely to tout both shyness and attention seeking. Finally, results generally showed that higher priced t-shirts were less likely to feature gender stereotypes than lower-priced t-shirts.

Originality/value

To the best of the authors’ knowledge, this is the first known study that has looked at the marketing of children’s clothes in retail environments with a specific focus on gender and gender stereotyping.

Details

Young Consumers, vol. 23 no. 3
Type: Research Article
ISSN: 1747-3616

Keywords

Article
Publication date: 7 November 2016

Congying Guan, Shengfeng Qin, Wessie Ling and Guofu Ding

With the developments of e-commerce markets, novel recommendation technologies are becoming an essential part of many online retailers’ economic models to help drive…

1856

Abstract

Purpose

With the developments of e-commerce markets, novel recommendation technologies are becoming an essential part of many online retailers’ economic models to help drive online sales. Initially, the purpose of this paper is to undertake an investigation of apparel recommendations in the commercial market in order to verify the research value and significance. Then, this paper reviews apparel recommendation techniques and systems through academic research, aiming to acquaint apparel recommendation context, summarize the pros and cons of various research methods, identify research gaps and eventually propose new research solutions to benefit apparel retailing market.

Design/methodology/approach

This study utilizes empirical research drawing on 130 academic publications indexed from online databases. The authors introduce a three-layer descriptor for searching articles, and analyse retrieval results via distribution graphics of years, publications and keywords.

Findings

This study classified high-tech integrated apparel systems into 3D CAD systems, personalised design systems and recommendation systems. The authors’ research interest is focussed on recommendation system. Four types of models were found, namely clothes searching/retrieval, wardrobe recommendation, fashion coordination and intelligent recommendation systems. The forth type, smart systems, has raised more awareness in apparel research as it is equipped with advanced functions and application scenarios to satisfy customers. Despite various computational algorithms tested in system modelling, existing research is lacking in terms of apparel and users profiles research. Thus, from the review, the authors have identified and proposed a more complete set of key features for describing both apparel and users profiles in a recommendation system.

Originality/value

Based on previous studies, this is the first review paper on this topic in this subject field. The summarised work and the proposed new research will inspire future researchers with various knowledge backgrounds, especially, from a design perspective.

Details

International Journal of Clothing Science and Technology, vol. 28 no. 6
Type: Research Article
ISSN: 0955-6222

Keywords

Article
Publication date: 2 March 2010

Wendy Moody, Peter Kinderman and Pammi Sinha

This study sets out to explore the application of psychological research methods (as yet not applied) in the fashion arena. The aim of this project is to quantify…

8746

Abstract

Purpose

This study sets out to explore the application of psychological research methods (as yet not applied) in the fashion arena. The aim of this project is to quantify, formalise and explore the causal relationships between clothing style, preference, personality factors, emotions and mood with a view to a better understanding of the psychological profile of the fashion consumer.

Design/methodology/approach

Using a uniformly composed sample of females, explorative quantitative research was carried out. Two sets of questionnaires were administered to the sample to examine emotion, mood and personality before trying on a set of eight garments categorized according to style; and again afterwards to examine emotion and mood while wearing each outfit. Photographs of participants were taken wearing each of the outfits. Participants then ranked the eight outfits in order of preference. SPSS analysis identified relationships and preference indicators.

Findings

The results indicated strong relationships between mood and significant relationships between three out of five personality factors and clothing style preference; mood was a significant predictor of preference, whilst personality was moderate.

Research limitations/implications

The research methodology necessitated lengthy time commitments from the participants and therefore limited the sample size, making generalization difficult. Based on the findings, the research requires further exploration of methods for practical application with a larger sample size.

Practical implications

Personality, emotion and mood were shown to be managed and reflected through clothing with implications for assistance in consumer clothing decisions, service training, and strategies for personal shoppers, market segmentation and design.

Originality/value

The methodology derived from a combination of research methods coupled with actual wearing experience, previously not studied together. This is original and demonstrates how important this combination is in order to fully appreciate the psychological profile of the fashion consumer.

Details

Journal of Fashion Marketing and Management: An International Journal, vol. 14 no. 1
Type: Research Article
ISSN: 1361-2026

Keywords

1 – 10 of over 14000