Assessment and Semantic Categorization of Fabric Visual Texture Preferences

Kodžoman, Duje; Hladnik, Aleš; Čuden, Alenka Pavko; Čok, Vanja

doi:10.2478/aut-2022-0006

Cited by 5 publications

(6 citation statements)

References 48 publications

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“…These results were similar to the ones of our preliminary study, where knitted rib was the second most attractive visual texture, which was semantically described as calm, appealing, and harmonious, with an emphasis on the homogenized structure, and boiled wool scored high results on the negative spectrum of adjectives (unattractive, inharmonious, unsophisticated) [38].…”

Section: Fabric Texture Perception and Preferencesupporting

confidence: 89%

“…The present study is the continuation of several preliminary studies conducted online. The first study was on color preference [37], the second on the visual texture of fabrics [38], the third on the odor preference of fabrics, and the fourth was a study on taste preferences. The goal of the preliminary studies was to narrow down the number of samples we ultimately used.…”

Section: Methodsmentioning

confidence: 99%

“…Due to the complexity of the research problem, it had to be divided into several phases. The results from the previous (preliminary) phase in which participants mostly assessed their mental representations of the sensations were published in [37,38]. The present paper presents the results of the second phase, in which the participants interacted with the fabrics.…”

Section: Introductionmentioning

confidence: 94%

“…A snapshot of the samples can be seen in Figure 2. Six texture samples were selected according to the results of a preliminary study [38] of fabric visual texture preferences. The procedure for this study was adopted from Nagamachi [39] and Karlsson [40].…”

Section: Samplesmentioning

confidence: 99%

“…The three most attractive visual textures of fabrics were crochet, knitted rib, and cloqué jacquard, while the least attractive were boiled wool, suede, and canvas. For Phase II of our research, these six fabrics were then produced using various manufacturing technologies; for the influential factors that define the textures see [38], while the fabric composition can be found in Figure 3.…”

Section: Samplesmentioning

confidence: 99%

See 4 more Smart Citations

Fabric Attractiveness Using Four Sensory Evaluators

Kodžoman,

Čok,

Podlesek

et al. 2023

Fibres &Amp; Textiles in Eastern Europe

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All senses elicit emotional responses to goods, services, and the environment. They also play an important role in the process of fashion design and its evaluation. This research is a continuation of several preliminary studies we conducted online to define three attractive and three unattractive colors, textures, smells, sounds, and tastes. In the present study, a sample of textile engineering and fashion design students and experts (N = 54) assessed four groups of 6 fabric samples (sensory evaluators) selected based on the results of the preliminary studies. Each group of fabrics was assessed in one of four sensory modalities (except taste). Two semantic differentials were used to assess each sensory modality: attractive/unattractive and boring/interesting in the case of color, insensitive/sensitive in the case of texture, disturbing/calming in the case of sound, and cheap/luxurious in the case of smell. We found that among the fabrics in six different colors, the pink fabric was the most attractive. Of the six textures presented, the knitted rib texture was found to be the most attractive to touch. The scent of lemon essential oil was perceived as the most attractive among the six scents used, and the friction sound of suede leather was perceived as the most attractive among the six friction sounds of fabrics. Cluster analysis showed that the attractiveness of scents and colors of six fabric samples was highly differentiated and (almost) each sample was perceived as unique, while the attractiveness of the texture and sound of different samples was less differentiated and the samples were divided into only two groups. This suggests that discrimination of fabric attractiveness may be better in some sensory evaluators/modalities than in others. The results of this study will be useful for further research on the integration of different sensory modalities in fabric perception and garment preferences.

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Section: Fabric Texture Perception and Preferencesupporting

confidence: 89%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 94%

Section: Samplesmentioning

confidence: 99%

Section: Samplesmentioning

confidence: 99%

See 3 more Smart Citations

Fabric Attractiveness Using Four Sensory Evaluators

Kodžoman,

Čok,

Podlesek

et al. 2023

Fibres &Amp; Textiles in Eastern Europe

Self Cite

View full text Add to dashboard Cite

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Modeling the relationship between fabric textures and the evoked emotions through different sensory perceptions

Zeng,

Wang,

Qiao

et al. 2024

Journal of Engineered Fibers and Fabrics

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Texture represents the surface quality of fabrics, which is one of the key factors for textiles design. Fabric texture can be perceived via sensory perceptions, like vision and touching, causing different psychological feelings and emotions. This paper aimed to model the correlation between fabric textures and the evoked emotions through different sensory perceptions. Firstly, 20 subjects were required to make sensory evaluation on 10 fabric samples, rating fabric textures and the induced emotions via visual and visual-tactile perceptions. Then, the differences in sensory evaluation on fabric textures and the evoked emotions were analyzed. The results showed that only by visual perception, the visual effects dominate the evaluation on fabric textures and emotions. Pile fabrics that look warm can induce positive emotions. By visual-tactile perception, the sensation of contact between fabric and skin accounts due to the intervention of tactile perception. Soft and smooth fabrics, like coral fleece and velvet can stimulate positive emotions. Finally, the emotion-fabric textures model for pleasure and arousal was established using stepwise regression analysis. It’s revealed that only by visual perception, cold/warm had a significant positive effect on pleasure, while no textures were found that have a significant impact on arousal. By visual-tactile perception, both hard/soft and rough/smooth had significant positive impact on pleasure, while thick/thin had a significant negative influence on arousal. The present findings can help direct textiles design, production and sales, so as to meet the specific requirements.

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Research on T-shirt-style design based on Kansei image using back-propagation neural networks

Xu,

Ren,

Chen

2023

AUTEX Research Journal

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Users’ Kansei image preferences have become one of the most important factors influencing purchase decisions. However, defining Kansei image can be complex. To address this issue, researchers have widely applied back-propagation neural networks due to their capacity to handle extensive data, adaptively adjust weights and biases, conduct multi-class classification and regression predictions, and offer interpretability analysis, among other features. In this study, a clothing-style design model based on users’ Kansei image cognition is proposed, using collarless T-shirts as an example. Furthermore, the attributes of T-shirt patterns are quantified using parametric graphics principles, and a semantic scale system for emotions is established through user research. The quantified sample data and corresponding semantic scale scores are then used as inputs for training a back-propagation neural network algorithm. Consequently, a design model grounded in users’ Kansei image cognition is developed, resulting in five optimal clothing design forms across various Kansei image categories. Additionally, the styles are showcased through the Style 3D platform, and the design evaluation is presented using radar charts. The results demonstrate that the five female T-shirt designs generated by the model align with users’ style preferences based on Kansei image.

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Assessment and Semantic Categorization of Fabric Visual Texture Preferences

Cited by 5 publications

References 48 publications

Fabric Attractiveness Using Four Sensory Evaluators

Fabric Attractiveness Using Four Sensory Evaluators

Modeling the relationship between fabric textures and the evoked emotions through different sensory perceptions

Research on T-shirt-style design based on Kansei image using back-propagation neural networks

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