3D modeling design and rapid style recommendation of polo shirt based on interactive genetic algorithm

Zhang, Zhuo; Cong, Honglian

doi:10.1177/1558925020966664

Cited by 5 publications

(6 citation statements)

References 9 publications

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“…If fitness is better than the global best Then (10) Update the global best hyperparameters (11) end ( 12) end ( 13) end (14) For particle in population do (15) Update particle velocity and position using the PSO formula ( 16) end (17) end (18)…”

Section: Proxy Model Flowchart and Pseudocodementioning

confidence: 99%

“…Unlike the GA, the IGA is not limited to solving problems with clearly defined formulas but is also able to deal with some problems that cannot be clearly defined by formulas. Currently, the IGA has been widely applied in automatic terrain generation systems [11], 3D gaming model design [12], fashion design [13,14], and music melody composition [15], etc.…”

Section: Introductionmentioning

confidence: 99%

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3D Vase Design Based on Interactive Genetic Algorithm and Enhanced XGBoost Model

Wang,

2024

Mathematics

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The human–computer interaction attribute of the interactive genetic algorithm (IGA) allows users to participate in the product design process for which the product needs to be evaluated, and requiring a large number of evaluations would lead to user fatigue. To address this issue, this paper utilizes an XGBoost proxy model modified by particle swarm optimization and the graphical interaction mechanism (GIM) to construct an improved interactive genetic algorithm (PXG-IGA), and then the PXG-IGA is applied to 3D vase design. Firstly, the 3D vase shape has been designed by using a bicubic Bézier surface, and the individual genetic code is binary and includes three parts: the vase control points, the vase height, and the texture picture. Secondly, the XGBoost evaluation of the proxy model has been constructed by collecting user online evaluation data, and the particle swarm optimization algorithm has been used to optimize the hyperparameters of XGBoost. Finally, the GIM has been introduced after several generations, allowing users to change product styles independently to better meet users’ expectations. Based on the PXG-IGA, an online 3D vase design platform has been developed and compared to the traditional IGA, KD tree, random forest, and standard XGBoost proxy models. Compared with the traditional IGA, the number of evaluations has been reduced by 58.3% and the evaluation time has been reduced by 46.4%. Compared with other proxy models, the accuracy of predictions has been improved up from 1.3% to 20.2%. To a certain extent, the PXG-IGA reduces users’ operation fatigue and provides new ideas for improving user experience and product design efficiency.

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Section: Proxy Model Flowchart and Pseudocodementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

3D Vase Design Based on Interactive Genetic Algorithm and Enhanced XGBoost Model

Wang,

2024

Mathematics

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“…Hong et al . (2018) and Zhuo and Honglian (2020) proposed methods that perform pattern deformation using the pattern dimension prediction function. However, it has been difficult to use such AI-based methods because the number of training data has usually been insufficient for machine learning.…”

Section: Introductionmentioning

confidence: 99%

“…Wang et al (2020) used fuzzy logic and artificial neural network to predict the primary dimensions of pants patterns, achieving higher accuracy than backpropagation artificial neural networks. Hong et al (2018) and Zhuo and Honglian (2020) proposed methods that perform pattern deformation using the pattern dimension prediction function. However, it has been difficult to use such AI-based methods because the number of training data has usually been insufficient for machine learning.…”

Section: Introductionmentioning

confidence: 99%

Automatic generation of parametric patterns from grading patterns using artificial intelligence

Oh,

Kim

2023

IJCST

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PurposeThis study aims to automate the process of converting grading patterns into parametric patterns using artificial intelligence and to objectively evaluate the fitness of the converted patterns.Design/methodology/approachThe developed system consists of a user interface that defines input data by importing multi-size grading patterns, an artificial neural network that learns the relationship between human body size and pattern geometry, and a module that converts training results into parametric patterns. In order to evaluate the fitness of the generated pattern, an objective fitting evaluation method using drape simulation was developed.FindingsThe body sizes of the wearer were input to the converted parametric pattern to generate a customized pattern. Resulting pattern showed a better fit than the grading pattern on the off-average body model.Research limitations/implicationsIn this study, a method has been developed that enables the users with minimal pattern drafting knowledge to convert grading patterns into parametric patterns using artificial intelligence and drape simulation. The human body's symmetry and the physical properties of fabric were not considered.Originality/valueThe system developed in this study requires less data compared to existing methods that attempt to design clothing patterns with machine learning. In addition, it was possible to evaluate pattern fitness on various body models through drape simulation based fit evaluation process for the first time.

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“…The results show that the proposed method has better performance than that of the traditional collaborative filtering recommendation algorithm. Zhuo and Honglian 38 developed a rapid style recommendation, which is applied to recommend the favorite polo shirt styles for users. Hong et al.…”

mentioning

confidence: 99%

Development of novel fashion design knowledge base by integrating conflict rule processing mechanism and its application in personalized fashion recommendations

Xue

Jin

Hong

et al. 2022

Textile Research Journal

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Currently, consumers are increasing the demand for personalized fashion recommendation systems, especially in e-commerce. The success of fashion recommendation largely relies on the fashion design knowledge base, which is the modelling of the professional knowledge and experience of fashion designers. As fashion products are rather emotional and easily influenced by fashion trends, fashion design knowledge bases always involve rich fashion-style words and various garment component elements, which results in conflict rules in personalized fashion recommendations. For system users, the recommendations cannot fully meet their personalized needs. In this context, this article proposes a novel garment design knowledge base by integrating the conflict rule processing mechanism and its application to the personalized fashion recommendation system. The proposed research methodology of the processing mechanism is based on subjective evaluation and fuzzy logic. Firstly, through the subjective evaluation by an expert group, the relationship between fashion-style words and garment component elements is established. After that, the conflict categories are identified and then the relationship between conflict categories and garment component elements is established. As the experimental data obtained from the subjective evaluation are semantics, fuzzy logic is employed to quantify and model the relationships. Finally, the established processing mechanism of conflict rules is applied to establish a personalized dress recommendation system in order to validate its performance. The experimental results show that the proposed mechanism is feasible and able to enhance the success of the recommendation, which can be further applied to the recommendation of all kinds of garments and other industrial products.

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3D modeling design and rapid style recommendation of polo shirt based on interactive genetic algorithm

Cited by 5 publications

References 9 publications

3D Vase Design Based on Interactive Genetic Algorithm and Enhanced XGBoost Model

3D Vase Design Based on Interactive Genetic Algorithm and Enhanced XGBoost Model

Automatic generation of parametric patterns from grading patterns using artificial intelligence

Development of novel fashion design knowledge base by integrating conflict rule processing mechanism and its application in personalized fashion recommendations

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