TY - SER
KW - Adversarial networks
KW - Algorithm model
KW - Artificial intelligence
KW - Bamboo
KW - Bamboo weaving patterns
KW - Blue calico
KW - Case-studies
KW - Chinese people
KW - Co-design
KW - Computer graphics
KW - Computer image processing
KW - Computer science
KW - Computer Vision
KW - Computers
KW - Cotton fabrics
KW - Deep learning
KW - Design ethnography
KW - Digital cultural heritage
KW - Employment
KW - Evaluation metrics
KW - Experience-centred design (ECD)
KW - Generative adversarial networks
KW - Hci researches
KW - Human computer interaction
KW - Human computer interaction (HCI)
KW - Image generations
KW - Image processing
KW - Intangible Cultural Heritage Protection
KW - Intangible cultural heritage regeneration
KW - Intangible cultural heritages
KW - Jiangxi Province
KW - Learning systems
KW - machine learning
KW - New approaches
KW - Pattern designs
KW - Practical method
KW - Printed patterns
KW - Printing and dyeing
KW - Research through design (RtD)
KW - Stress intensity factors
KW - Traditional Chinese painting
KW - User satisfaction
KW - Weaving patterns
AU - Y. Wang
AU - R. Fu
AB - As a traditional handicraft printing and dyeing product of the Han nationality, blue calico has been included in the first batch of national intangible cultural heritage list. Blue printed pattern is famous for its blue and white color characteristics. However, due to monotonous and old pattern design, lack of innovation and other factors, blue calico cannot adapt to the contemporary aesthetic habits, resulting in difficulties in inheritance and regeneration. In order to solve this problem, this paper aims at redesigning and activating the blue calico by combining the traditional pattern with the modern graphic design pattern through machine learning and computer image processing technology. With Inception Score and user satisfaction survey as the evaluation metrics, feasibility of computer image processing technology for the reconstruction of intangible cultural heritage image generation is verified. Finally, design value of generated patterns is proved, and a research model of the relationship between computer image processing technology and intangible cultural heritage design is established.
C1 - 8th International Conference on Culture and Computing, C and C 2020, held as part of the 22nd International Conference on Human-Computer Interaction, HCII 2020
DO - 10.1007/978-3-030-50267-6_32
LA - English
N1 - Journal Abbreviation: Lect. Notes Comput. Sci. Pages: 438 Publication Title: Lect. Notes Comput. Sci.
N2 - As a traditional handicraft printing and dyeing product of the Han nationality, blue calico has been included in the first batch of national intangible cultural heritage list. Blue printed pattern is famous for its blue and white color characteristics. However, due to monotonous and old pattern design, lack of innovation and other factors, blue calico cannot adapt to the contemporary aesthetic habits, resulting in difficulties in inheritance and regeneration. In order to solve this problem, this paper aims at redesigning and activating the blue calico by combining the traditional pattern with the modern graphic design pattern through machine learning and computer image processing technology. With Inception Score and user satisfaction survey as the evaluation metrics, feasibility of computer image processing technology for the reconstruction of intangible cultural heritage image generation is verified. Finally, design value of generated patterns is proved, and a research model of the relationship between computer image processing technology and intangible cultural heritage design is established.
PB - Springer
PY - 2020
SN - 03029743 (ISSN); 9783030502669 (ISBN)
TI - A Methodological Reflection: Deconstructing Cultural Elements for Enhancing Cross-Cultural Appreciation of Chinese Intangible Cultural Heritage
UR - https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089166647&doi=10.1007%2f978-3-030-50267-6_32&partnerID=40&md5=14d1e75da7b7f6acffeae2db6d6c5593
VL - 12215 LNCS
ER -