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Multimodal perception of digital protective materials
by
BOCANCEA, VICTORIA
, LOGHIN, CARMEN MARIA
, MARIN, IRINA ELENA
in
Animation
/ Digital imaging
/ Digitization
/ Fabric analysis
/ Format
/ Material properties
/ Perception
/ Polyesters
/ Real time
/ Software
/ Statistical analysis
/ Textile industry
/ Virtual prototyping
2024
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Multimodal perception of digital protective materials
by
BOCANCEA, VICTORIA
, LOGHIN, CARMEN MARIA
, MARIN, IRINA ELENA
in
Animation
/ Digital imaging
/ Digitization
/ Fabric analysis
/ Format
/ Material properties
/ Perception
/ Polyesters
/ Real time
/ Software
/ Statistical analysis
/ Textile industry
/ Virtual prototyping
2024
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Do you wish to request the book?
Multimodal perception of digital protective materials
by
BOCANCEA, VICTORIA
, LOGHIN, CARMEN MARIA
, MARIN, IRINA ELENA
in
Animation
/ Digital imaging
/ Digitization
/ Fabric analysis
/ Format
/ Material properties
/ Perception
/ Polyesters
/ Real time
/ Software
/ Statistical analysis
/ Textile industry
/ Virtual prototyping
2024
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Journal Article
Multimodal perception of digital protective materials
2024
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Overview
The online clothing industry has gained popularity among consumers, and the perception of materials and equipment plays a crucial role in their purchasing decisions. Therefore, accurately representing their appearance in real-time is essential. This study aimed to subjectively evaluate 20 protective textile materials by translating their tactile characteristics into virtual prototypes. This was accomplished by scanning physical materials with an x-Tex scanner and processing them in KeyShot rendering software. Consequently, four scenarios featuring digital materials were created: S1-image, S2-video animation, S3-3D object, and S4-physical materials. Digital visual subjective evaluations were conducted for sensory analysis. Participants were asked to assess four visual and seven tactile characteristics using a seven-point Likert scale. Statistical analysis was employed to evaluate the sensory data collected through subjective testing. The results indicated that agreement values for the four scenarios ranged from 1.25 to 7.0, as illustrated in boxplot diagrams representing the subjects' agreement with the perceptual attributes. Pairwise comparisons of the S4-S1, S4-S2, and S4-S3 scenarios concerning the difference in means revealed that attributes FR with values of 0.045 (S1), RM with values of 0.063 (S1), CR with values of 0.028 (S1), CR with values of 0.039 (S2), and 0.052 (S3) are closely aligned with the actual values, as the values obtained from these scenarios closely approximate 0. In contrast, the values of the remaining attributes were close to 1, indicating the difficulty of translating these attributes into digital format and achieving accurate perception. Assessing textile material properties through digital images remains a challenging task that requires in-depth subjective analysis.
Publisher
The National Research & Development Institute for Textiles and Leather - INCDTP
Subject
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