Clothing Pattern Research Articles

The Consumerism Culture of the Younger Generation in Fashion

Fashion is one of the most widely known phenomena of everyday life, inextricably linked with art, communication, and mass culture. The scope of fashion includes clothing, forms of everyday life, cars, aesthetic and artistic tastes, etc. In most cases, researchers understand fashion as clothing patterns that are most popular in a specific historical period. A person always searches for his belonging, tries to identify himself with a social group that is a reference for him. Habit, following a model and imitation are the basis of self-determination, which ensures the rituality of culture and the mechanisms of its development and reproduction. Fashion helps to preserve cultural tradition, is a symbol of social status, directs behavior and sets the boundaries of what is permitted and desired, and acts as a means of achieving social recognition. In modern world, fashion has received much attention from both ordinary people and scientists. Being an interdisciplinary object, fashion attracts the attention of researchers from different fields of knowledge. More precisely than others, the essence and concept of fashion are reflected by those who create it. Therefore, the article studies and analyzes the understanding of fashion by famous couturiers. In conclusion, the author, according to literature materials, and combining the approaches considered, explain main attributes of the consumption culture of young generation. Keywords: fashion, consumption culture, youth, fashion industry, social recognition

Determining the thermal comfort of naturally ventilated state colleges located in Madhya Pradesh, India

ABSTRACT Through the establishment of optimal thermal conditions, educational institutions can develop an environment favourable to learning, concentration, and academic achievements. Additionally, comfortable temperatures can contribute to the overall well-being and satisfaction of both students and teachers, fostering a positive educational experience. In this study, we aimed to determine the impacts of environmental factors on students’ thermal comfort in three state colleges of Madhya Pradesh. A total of 784 students participated in a questionnaire study conducted during May (Summer season), August (Monsoon season), October (Autumn season), and December (Winter season) of 2023 to assess occupants’ degree of clothing, temperature preference, and metabolic rates. Indoor and outdoor temperatures, relative humidity, and air velocity were measured using an anemometer. Throughout the study period, the thermal comfort range was determined to be between 21.5°C and 28.5°C, with 25°C as the neutral temperature. It has been noted that the clothing pattern varies during the year (0.47-0.85 Clo). Additionally, implementation of the adaptation strategies, such as switching on and off fans or opening windows, helped lessen discomfort in the classroom. The findings indicate that, in contrast to the other seasons, the summers brought exceptionally high levels of heat discomfort to the occupants.

Research on design thinking of pleated clothing inspired by fractal geometry

PurposeThis paper summarizes the design thinking of pleated clothing, uses virtual software to simulate the pleated clothing process and clothing effect and applies the fractal geometry principle to conduct relevant experiments, which verifies the possibility of simulation software assisting pleated clothing design, improves research and development efficiency, lays a foundation for future process parameter collection to upgrade the pleated clothing database and realizes the diversity of digital innovative design of pleated clothing.Design/methodology/approachAccording to the principle of self-similarity and fractal dimension in fractal geometry, the design thinking of pleated clothing is put forward and the simulation folding of 3D digital technology is expanded. The design method takes traditional craft and digital technology as an example. The two-dimensional design thinking of pleated clothing is geometric crease thinking of fabric swatch and geometric expansion of basic clothing pattern. Three-dimensional modeling design thinking, such as based on the human body shape, geometric shape and folding mode. As well as digital design thinking, such as the angle of the fabric element and the perspective of garment pattern change.FindingsThis paper analyzes the Y structure of the similar shape “binary tree” in origami art, the principle of infinite folding with 45? As the unit and the point set capacity theory of Cantor concentric circles in the fractal dimension principle expands the design thinking of pleated clothing, applies a large number of experimental cases of design thinking inspired by the fractal geometry of pleated clothing and validates the possibility of simulation software assisting pleated clothing design.Research limitations/implicationsWe argue here that digital technology should continue to be used in a similar way for research and development in other clothing design-related processes in the future. When it comes to the possibilities for digital innovation in relation to pleated clothing, there is a lack of data for modeling the characteristics of such clothing and establishing the processing requirements. Thus, there is scope here for innovation breakthroughs in terms of both the art and the technology associated with clothing design, not to mention how the two are integrated. This paper has laid some potential foundations for this through its elaboration of fractal-inspired design in the context of pleated garments.Practical implicationsNumerous experiments were undertaken and digital simulation software was used to explore various potential designs in the paper. This confirmed the possibility of using simulation software to assist in the design of pleated clothing, which offers the scope for improved research and more efficient development. However, if the processing parameters for changes in the pleated fabric are not set in the software, it is impossible to automatically generate auxiliary clothes. The collection of processing parameters and the creation of a more comprehensive pleated clothing database should therefore be the focus of future research.Social implicationsThe paper is oriented toward future clothing design. There is some impact on research, practice and/or society. This opens up the possibility of using fractal geometry in the design of the folds and dimensional energy in pleated clothing. On the whole, the innovation point is clear and the idea is novel. By seeking the principles of science and technology, sensing the infinite possibilities, improving the design efficiency and inspiring innovative design thinking methods, in order to meet the diversity and personality needs of the external shape of the human body.Originality/valueThe concave and convex texture of pleated fabric is geometric and decorative. It has a direct reference value for pleated clothing design by using the concepts of partial and whole in fractal geometry and the quantity and energy conversion in fractal dimension space. Due to the influence of clothing intelligent manufacturing policy, there is a lack of data sorting for the modeling characteristics and process requirements of pleated clothing, and there is innovative design thinking that needs to be integrated with technology and art, which lays a foundation for the future collection of process parameters to upgrade the pleated clothing database.

Application and Innovative Design Strategies of Cultural Elements in the Costume Patterns of Qing Dynasty Emperors

This article deeply explores the application and innovative design of cultural elements in the clothing patterns of Qing Dynasty emperors. Firstly, it analyzes the richness and symbolism of Qing Dynasty emperor clothing patterns, the uniqueness and aesthetic value of colors, as well as the exquisite and innovative craftsmanship. The second point is to point out the limitations of traditional element application, cultural connotation misinterpretation and shallowness, as well as the disconnect between market adaptability and consumer demand in current design. Propose optimization measures to address these issues, aiming to promote the widespread application and inheritance of cultural elements of Qing Dynasty emperor costume patterns in modern design.

Design of geometric flower pattern for clothing based on deep learning and interactive genetic algorithm

Abstract Geometric and floral models are an important part of clothing and have been used for thousands of years. Although the styles of geometric models and flower models have undergone changes over the centuries, they are still one of the important factors of clothing patterns, the important carrier of aesthetics, and the manifestation of people’s spiritual views and cultural needs. The development and application of digital printing technology have freed people from excessive dependence on sewing and embroidery processes. Therefore, while deeply studying the design of clothing patterns, this work sorted and analyzed the geometric flower models of clothing through interactive genetic algorithms, and optimized programming to enrich the models of clothing with geometric textures. The results showed that the deviation value of geometric flower pattern design was constantly decreasing, while the optimal strategy value was constantly increasing. The mean deviation value was 0.82, which was a decrease of 0.21 on the seventh day compared with the first day; the mean value of the optimal strategy value was 0.84, which was an increase of 0.19 on the seventh day compared with the first day. The visual effect and creativity of the clothing flower pattern design under the interactive genetic algorithm are better than the traditional flower pattern design, and the visual effect and creativity under the interactive genetic algorithm are 9% higher than the traditional one.

Optimization of Clothing Pattern Design Combining Deep Learning and CAD

Optimization of Clothing Pattern Design Combining Deep Learning and CAD

Study of the use of neural network in combination with graphical programs in light industry

Technology, currently at the peak of its development, provides an opportunity to increase the level of education of modern man. As a consequence, the development of new clothing models using neural networks is also becoming a more efficient way to optimize design processes. By applying neural networks, results can be achieved quickly and easily. Artificial intelligence empowers and optimizes work in the fashion industry: it recognizes clothes from photos, accesses virtual fitting sessions, and, without much effort, easily selects the perfect size. The program will automatically design the pattern and technically reproduce patterns by size, height and fullness. Artificial intelligence will require less creative work from the author, and the designers themselves will be able to spend more time on their creativity. The research paper utilizes Microsoft Bing to facilitate the creation of new designs for clothing patterns. It is an artificial intelligence that can be used to create images, solve problems and get new ideas. With the help of this program it is planned to create an experimental series of Kyrgyz national costumes, the details of which will be designed in the graphic program of Grafic 12 clothing designer.

Semiotic Analysis of Cantonese and Middle Eastern Embroidery Patterns in Clothing

Semiotic Analysis of Cantonese and Middle Eastern Embroidery Patterns in Clothing

Palembang songket fabric motif image detection with data augmentation based on ResNet using dropout

A good way to spread knowledge about Palembang songket woven cloth patterns is to use information technology, especially artificial intelligence technology. This study's main goal is to develop a ResNet model with dropout regularization methods and find out how dropout regularization affects the ResNet model for detecting Palembang songket fabric motif with more data. Data was collected in places like tujuh saudara songket, Zainal songket, songket PaSH, AMS songket, and batik, Ernawati songket, Nabilah collections, Ilham songket, and Marissa songket. We used eight class of data for this research. A dataset of 7,680 data for training, 960 data for validation, and 960 data for testing is a dataset that has been prepared to be implemented in experiments. In the final results, the experimental results for DResNet demonstrated that accuracy at the training stage was 92.16%, accuracy at the validation stage was 78.60%, and accuracy at the submission stage was 80.3%. The experimental results also show that dropouts are able to increase the accuracy of the ResNet model by adding +1.10% accuracy in the training process, adding +1.80% accuracy in the validation process, and adding +0.40% accuracy in the testing process.

Segmentation of ethnic clothing patterns with fusion of multiple attention mechanisms

To address the challenges posed by diverse pattern-background elements, intricate details, and complex textures in the semantic segmentation of ethnic clothing patterns, this research introduces a novel semantic segmentation network model called MST-Unet (Mixed Swin Transformer U-net). The proposed model combines a U-shaped network structure with multiple attention mechanisms. The upper layers of the model employ classical convolutional operations, focusing on local relationships in the initial layers containing high-resolution details. In deeper layers, Swin Transformer modules are utilized, capable of efficient feature extraction with smaller spatial dimensions, maintaining performance while reducing computational burden. An attention gate mechanism is integrated into the decoder, contributing to enhanced performance in ethnic clothing pattern segmentation tasks by allowing the model to better capture crucial image features and achieve precise segmentation results. In visual comparisons of segmentation results, our proposed model demonstrates superior performance. The segmentation results exhibit more complete preservation of edge contours and fewer misclassifications in irrelevant regions within the images. In qualitative and quantitative experiments conducted on the ethnic clothing pattern dataset, our model achieves the highest Dice score for segmentation results in all four subclasses of ethnic clothing patterns. The average Dice score of our model reaches an impressive 89.80%, surpassing other algorithms in the same category. When compared to Deeplab_V3+, ResUnet, SwinUnet, and Unet networks, our model outperforms them by 7.72%, 5.09%, 5.05%, and 0.67%.

A clothing pattern generating framework based on scanned human body model

PurposeAccurate and automatic clothing pattern making is very important in personalized clothing customization and virtual fitting room applications. Clothing pattern generating as well as virtual clothing simulation is an attractive research issue both in clothing industry and computer graphics.Design/methodology/approachPhysics-based method is an effective way to model dynamic process and generate realistic clothing animation. Due to conceptual simplicity and computational speed, mass-spring model is frequently used to simulate deformable and soft objects follow the natural physical rules. We present a physics-based clothing pattern generating framework by using scanned human body model. After giving a scanned human body model, first, we extract feature points, planes and curves on the 3D model by geometric analysis, and then, we construct a remeshed surface which has been formatted to connected quad meshes. Second, for each clothing piece in 3D, we construct a mass-spring model with same topological structures, and conduct a typical time integration algorithm to the mass-spring model. Finally, we get the convergent clothing pieces in 2D of all clothing parts, and we reconnected parts which are adjacent on 3D model to generate the basic clothing pattern.FindingsThe results show that the presented method is a feasible way for clothing pattern generating by use of scanned human body model.Originality/valueThe main contribution of this work is twofold: one is the geometric algorithm to scanned human body model, which is specially conducted for clothing pattern design to extract feature points, planes and curves. This is the crucial base for suit clothing pattern generating. Another is the physics-based pattern generating algorithm which flattens the 3D shape to 2D shape of cloth pattern pieces.

CONSTRUCTING BATANG BATIK MOTIFS USING TURTLE GRAPHICS ALGORITHMS

During the COVID–19 pandemic, many activities were carried out digitally, including storing batik motifs to maintain the cloth pattern's sustainability. The samples were Batang Batik motifs of grapes, Jamblang Papat and Kawung Jenggot. The study aimed to store batik motifs in the form of computer programs with turtle graphics algorithms to ease the batik motif delivery because of the smaller memory storage. Computer programmers are needed to create batik patterns similar to Batang Batik patterns. Python programming uses turtle graphics to paint curves and generate graphics. The results of this study indicated that Batang Batik motifs can be made using turtle graphics without losing the characteristics of the batik itself. This finding can be used for more efficient storage of memory. The quality was also good when it was scaled up and down. This study has successfully created Grape, Jambang Prapat, and Kawung Jenggot motifs using turtle graphics algorithms in Python. The picture quality of the turtle graphics-scaled reconstructed image was equivalent to that of a photo image.

Exploring the relationship between color and form in the design of women’s Latin dance costumes

This article delves into the complex world of designing women's Latin dance costumes, highlighting the paramount importance of harmonizing current fashion trends with the essential requirements of comfort, flexibility, and the need to emphasize the dancer's graceful movements. The objective of this study was to create few models of Latin dance costumes. To forecast how the users and viewers would perceive Latin dance outfits, an on-line survey was conducted. A regression model was applied to analyze how color and shape interact in the creation of Latin dance costumes. The article focuses on key aspects of costume design, covering an in-depth study of silhouettes and colors and their perception by viewers. Designers are encouraged to focus their creative efforts on prioritizing the comfort and freedom of movement of the dancers, adapting to ever-evolving societal and cultural changes, and exploring innovative solutions to overcome the challenges and limitations inherent in costume creation. The regression model can be used to predict with enough accuracy users' and viewers' opinions on the use of Latin dance costumes. Embracing these results, designers are ready to produce remarkable, comfortable clothing patterns that authentically capture the splendor and diversity of Latin dance culture.

Research on the image design of clothing patterns

Abstract In order to solve the problem of mismatch between consumers’ personalized needs and clothing pattern design, a method of clothing pattern image design was proposed based on Kansei engineering theory to obtain a perceptual consumer image. Then, a correlation model between clothing pattern design elements and perceptual images of young people was established through the quantitation theory type I, and the mapping relationship between the two and the degree of influence on consumer preference was presented by the diagram method. The paper-cut pattern of a T shirt is taken as an example to verify the feasibility of this research method. The results show that it not only provides designers with clear design indicators and references, but also makes the design process more objective and scientific.

A review of parametric clothing pattern CAD software methodology

PurposeThe main issue in the mass customization of apparel products is how to efficiently produce products of various sizes. A parametric pattern-making system is one of the notable ways to rectify this issue, but there is a lack of information on the parametric design itself and its application to the apparel industry. This study compares and analyzes three types of parametric clothing pattern CAD (P-CAD) software currently in use to identify the characteristics of each, and suggest a basic guideline for efficient and adaptable P-CAD software in the apparel industry.Design/methodology/approachThis study compared three different types of P-CAD software with different characteristics: SuperALPHA: PLUS(as known as YUKA), GRAFIS and Seamly2D. The authors analyzed the types and management methodologies of each software, according to the three essential components that refer to previous studies about parametric design systems: entities, constraints and parameters.FindingsThe results demonstrated the advantages and disadvantages of methodology in terms of three essential components of each software. Based on the results, the authors proposed five strategies for P-CAD development that can be applied to the mass customization of clothing.Originality/valueThis study is meaningful in that it consolidates and organizes information about P-CAD software that has previously been scattered. The framework used in this study has an academic value suggesting guidelines to analyze P-CAD systems.

Pattern Guided UV Recovery for Realistic Video Garment Texturing.

The fast growth of E-Commerce creates a global market worth USD 821 billion for online fashion shopping. What unique about fashion presentation is that, the same design can usually be offered with different cloths textures. However, only real video capturing or manual per-frame editing can be used for virtual showcase on the same design with different textures, both of which are heavily labor intensive. In this paper, we present a pattern-based approach for UV and shading recovery from a captured real video so that the garment's texture can be replaced automatically. The core of our approach is a per-pixel UV regression module via blended-weight multilayer perceptrons (MLPs) driven by the detected discrete correspondences from the cloth pattern. We propose a novel loss on the Jacobian of the UV mapping to create pleasant seams around the folding areas and the boundary of occluded regions while avoiding UV distortion. We also adopts the temporal constraint to ensure consistency and accuracy in UV prediction across adjacent frames. We show that our approach is robust to a variety type of clothes, in the wild illuminations and with challenging motions. We show plausible texture replacement results in our experiment, in which the folding and overlapping of the garment can be greatly preserved. We also show clear qualitative and quantitative improvement compared to the baselines as well. With the one-click setup, we look forward to our approach contributing to the growth of fashion E-commerce.

Physical and mental safety monitoring and protection of children with autism spectrum disorder: Intelligent clothing integrating early warning and rescue

Nowadays, the safety of special children has gradually become a hot spot of social concern. In this paper, aiming at the problems of autism spectrum disorder children who are easy to get lost and drown, intelligent monitoring clothing with lost warning and drowning rescue functions is designed. Firstly a clothing technology system based on multi-MCU and BeiDou dual-mode positioning was set up. Then according to their characteristics of physiology and psychology, CLO was used for virtual simulation design of color, pattern, and style of sample clothes. Finally, the product prototype of intelligent monitoring clothing was evaluated from various aspects. The results confirm that the clothing can meet the physical and psychological needs of these children. Its intelligent sensor positioning, data acquisition and transmission, and waterproof and rescue functions are designed accurately, which can not only play an early warning and protection role when children go beyond the fence and drown, but also reduce the monitoring burden of parents to a certain extent. This study also provides a reference for the design of intelligent monitoring clothing for special children.

Research on the Future Trends of the Integration of Artificial Intelligence and Fashion Design of Clothing

Abstract Along with the flow of clothing designer personnel, clothing style design technology will be lost, so the intelligent design of the clothing industry, with the development of artificial intelligence technology, has received great attention. In this paper, based on the real-time style migration algorithm to study and design the local pattern of clothing, based on the principle of real-time style migration of images with perceptual loss function, it is proposed to optimize the real-time style migration network by using the group normalization method to obtain the style migration image that is more in line with the visual habit. The fusion of the style migration image with the garment base map through Poisson fusion achieves the end-to-end intelligent design of garment local patterns. The AdaIN-based style migration network model designed in this paper has an average accuracy of 75.758% when trained. Then, the model is applied to the clothing fashion design to evaluate the effect of the garment. The average scores of the overall, front, side, and back evaluation of the dressing effect of the garment are 4.04, 4.15, 4.01, and 3.92, respectively. The garments show a better effect. AI technology will bring more innovative possibilities to the clothing fashion industry and inject new vitality into the fashion industry.

Design of metadata scheme for traditional Chinese clothing patterns for cultural digitization

Design of metadata scheme for traditional Chinese clothing patterns for cultural digitization

K-Means and Morphology Based Feature Element Extraction Technique for Clothing Patterns and Lines

K-Means and Morphology Based Feature Element Extraction Technique for Clothing Patterns and Lines