Development of a dress design knowledge base (DDKB) based on sensory evaluation and fuzzy logic

Xue, Ling; Hong, Yan; Pan, Zhijuan

doi:10.1108/ijcst-02-2020-0016

Cited by 15 publications

(7 citation statements)

References 29 publications

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“…In the fashion field, the application of sensory evaluation mainly focuses on fashion aesthetic design evaluation, comfort evaluation, and personalized recommendation. 22 This paper adopts the form of a questionnaire, and uses the expert sensory evaluation method to score the similarity of different parts of virtual T-shirts and real T-shirts. In the questionnaire, the experts were asked to score the real and virtual T-shirts; the scores of some of the sensory evaluation indicators of the experts are given in Table 3.…”

Section: Design and Extraction Of Evaluation Indicesmentioning

confidence: 99%

A model for predicting the similarity between real and virtual T-shirts based on sensory evaluation and image quantitative index evaluation

Jiang,

Hao,

Zhang

et al. 2023

Textile Research Journal

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Reported herein is a model for evaluating and predicting the similarity between real clothing and clothing simulated by the virtual fitting software Vidya, the aim being to estimate accurately the similarity between real and virtual clothing. Firstly, we make real T-shirts and virtual T-shirts. According to Kawabata Evaluation System test parameters, 24 kinds of digital fabrics were constructed, and 96 virtual T-shirts were modeled from these digital fabrics. Then, 24 real T-shirts were made from the corresponding fabric. After that, the similarity evaluation indexes of virtual T-shirts and real T-shirts were extracted. Expert evaluation and digital image processing were used to evaluate the visual sense of the images and extract the indices of the evaluation-site images. Finally, the principal component analysis (PCA)-backpropagation (BP) evaluation model was established. Based on PCA, effective evaluation indices for real and virtual T-shirts were selected to construct an evaluation index system of clothing modeling and a BP neural network evaluation model. After repeatedly debugging the number of neurons, the model was optimized with four hidden-layer neurons, and the overall correlation coefficient R of the model reached 0.91075. In this paper, an evaluation index system for real and virtual T-shirts was constructed and, based on the indices, a rapid method for evaluating the virtual fitting modeling effect based on the PCA-BP model was established, which also provides a reference for the whole process of modeling evaluation of other virtual fitting software.

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Section: Design and Extraction Of Evaluation Indicesmentioning

confidence: 99%

A model for predicting the similarity between real and virtual T-shirts based on sensory evaluation and image quantitative index evaluation

Jiang,

Hao,

Zhang

et al. 2023

Textile Research Journal

View full text Add to dashboard Cite

show abstract

“…Thus, efficient human-product interactions, aiming at offering decision support for designers by unveiling and applying the sophisticated quantified relationships between consumers' equivocal needs and product design parameters, have become a key to success in garment e-MC. Presently, diverse computational tools have been put forward to provide decision supports in key links of the personalized garment design process, such as design solution generation [26][27][28], fabric selection [29,30], colour coordination [31][32][33], fashion sketch design [34][35][36], garment pattern design [37][38][39][40][41][42], and so forth. For instance, in Ref.…”

Section: Introductionmentioning

confidence: 99%

Design of Customized Garments Towards Sustainable Fashion Using 3D Digital Simulation and Machine Learning-Supported Human–Product Interactions

Wang

Tao

Zeng

et al. 2023

Int J Comput Intell Syst

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This paper put forward a new interactive design approach for customized garments towards sustainable fashion using machine learning techniques, including radial basis function artificial neural network (RBF ANN), genetic algorithms (GA), probabilistic neural network (PNN), and support vector regression (SVR). First, RBF ANNs were employed to estimate the detailed human body dimensions to fulfill consumers’ ergonomics requirements. Next, the GA-based models were developed to generate the formalized design solutions following the consumer profiles (demands). Afterwards, the evaluation model was established to quantitatively characterize the relations between consumer profiles and garment profiles from the generated design solutions. The design solutions would be digitally demonstrated and recommended to the consumer following the evaluation results in descending order. Meanwhile, the PNN-based models were created to predict garment fitness based on virtual try-on. Moreover, the SVR-based self-adjustment mechanism was built to estimate and control garment design parameters according to the consumer’s feedback. Based on these mathematical models, the approach enhances the interactions among digital garment demonstration, the designer’s professional knowledge and the user’s perception to find out the most relevant design solution. The effectiveness of the new approach was verified by a real application case of leisure pants customization. The results show that the proposed method can powerfully support the designers’ quality personalized design solutions for consumers more accurately, fast, intelligently, and sustainably, compared with the existing approaches. More importantly, it also establishes an effective and reliable communication channel and mechanism among consumers, fashion designers, pattern designer, and garment producer.

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“…Hakka costume is an important part of Chinese national costume, as a splendid flower in the grand view garden of Chinese national costume, blossoming quietly in the land of China [1]. It retains the traces of the traditional clothing of the Han Chinese in the Central Plains and draws on the beneficial clothing components of the indigenous people in the western Fujian area, adapting to the special mountainous environment of the region [2]. Its uniqueness lies in its natural simplicity, which conveys the traditional Chinese ideology and dress aesthetic habits in a plain and innocent dress language [3].…”

Section: Introductionmentioning

confidence: 99%

The Application of Traditional Hakka Clothing Cultural Elements in Modern Clothing Design in Western Fujian Based on Image Feature Extraction Technology

Shi

2023

Applied Mathematics and Nonlinear Sciences

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In this paper, by applying the SIFT algorithm to the color category, texture and shape features of the dress pattern image for feature extraction and eliminating the low contrast texture feature points of the Taylor series expansion, using the statistics of the grayscale covariance matrix as the texture features. Based on the SIFT algorithm, the SURF feature extraction algorithm is proposed. The ideas of the Hessian matrix, determinant value approximation (DoH) and integral image (IGI) classifier are integrated to construct the feature fusion algorithm. Finally, the experimental results of several algorithms are compared and analyzed by taking the traditional dress pattern of the western Fujian Hakka family as the experimental object. The results show that among all the fusion algorithms, the SURF+IGI algorithm achieves an average recognition rate of 0.8914, which is the best performance. And the AUC value of its test set is 0.9445 when the learning rate is 0.005. The research in this paper meets the demand of extracting and applying the cultural elements of the traditional dresses of the Hakka family in western Fujian in modern dress design.

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Development of a dress design knowledge base (DDKB) based on sensory evaluation and fuzzy logic

Cited by 15 publications

References 29 publications

A model for predicting the similarity between real and virtual T-shirts based on sensory evaluation and image quantitative index evaluation

A model for predicting the similarity between real and virtual T-shirts based on sensory evaluation and image quantitative index evaluation

Design of Customized Garments Towards Sustainable Fashion Using 3D Digital Simulation and Machine Learning-Supported Human–Product Interactions

The Application of Traditional Hakka Clothing Cultural Elements in Modern Clothing Design in Western Fujian Based on Image Feature Extraction Technology

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