Detection of Traditional Costumes: A Computer Vision Approach
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Traditional attire has assumed a pivotal role within the contemporary fashion industry. The objective of this study is to construct a computer vision model tailored to the recognition of traditional costumes originating from five distinct countries, namely India, Korea, Japan, Tanzania, and Vietnam. Leveraging a dataset comprising 1,608 images, we proceeded to train the cutting-edge computer vision model YOLOv8. The model yielded an impressive overall mean average precision (MAP) of 96%. Notably, the Indian sari exhibited a remarkable MAP of 99%, the Tanzanian kitenge 98%, the Japanese kimono 92%, the Korean hanbok 89%, and the Vietnamese ao dai 83%. Furthermore, the model demonstrated a commendable overall box precision score of 94.7% and a recall rate of 84.3%. Within the realm of the fashion industry, this model possesses considerable utility for trend projection and the facilitation of personalized recommendation systems.
Abstract
Traditional attire has assumed a pivotal role within the contemporary fashion industry. The objective of this study is to construct a computer vision model tailored to the recognition of traditional costumes originating from five distinct countries, namely India, Korea, Japan, Tanzania, and Vietnam. Leveraging a dataset comprising 1,608 images, we proceeded to train the cutting-edge computer vision model YOLOv8. The model yielded an impressive overall mean average precision (MAP) of 96%. Notably, the Indian sari exhibited a remarkable MAP of 99%, the Tanzanian kitenge 98%, the Japanese kimono 92%, the Korean hanbok 89%, and the Vietnamese ao dai 83%. Furthermore, the model demonstrated a commendable overall box precision score of 94.7% and a recall rate of 84.3%. Within the realm of the fashion industry, this model possesses considerable utility for trend projection and the facilitation of personalized recommendation systems.
참고문헌 (23)
- Han, Xintong, "Viton: An image-based virtual try-on network", Proceedings of the IEEE conference on computer vision and pattern recognition, pp.7543~7552 (2018)
- Hadi Kiapour, M., "Where to buy it : Matching street clothing photos in online shops", Proceedings of the IEEE international conference on computer vision, pp.3343~3351 (2015)
- Huang, Junshi, "Cross-domain image retrieval with a dual attribute-aware ranking network", Proceedings of the IEEE international conference on computer vision, pp.1062~1070 (2015)
- Liu, Ziwei, "Deepfashion: Powering robust clothes recognition and retrieval with rich annotations", Proceedings of the IEEE conference on computer vision and pattern recognition, pp.1096~1104 (2016)
- Ren, Shuyun, "Demand forecasting in retail operations for fashionable products : methods, practices, and real case study", Annals of Operations Research, 291, pp.761~777 (2020)
- Audita Handini, "The fashion development process for traditional costumes in the contemporary global fashion market", Journal of Global Fashion Marketing, 14(1), pp.108~122 (2023), 한국마케팅과학회[DOI]
- Liu, Yongru, "Application of Jiangxi intangible cultural heritage in modern fashion design", 2017 3rd International Conference on Economics, Social Science, Arts, Education and Management Engineering (ESSAEME 2017) (2017), Atlantis Press
- Tajuddin, Fatjri Nur, "Cultural and social identity in clothing matters"different cultures, different meanings", European Journal of Behavioral Sciences, 1(4), pp.21~25 (2018)
- "The Significance of Traditional Clothing Across Cultures"[URL]
- Terven J, "Cordova-Esparza D. A Comprehensive Review of YOLO: From YOLOv1 to YOLOv8 and Beyond", Beyond (2023)
- Cheng, Wen-Huang, "Fashion meets computer vision: A survey", ACM Computing Surveys (CSUR), pp.1~41 (2021)
- Piacentini, Maria, "Symbolic consumption in teenagers' clothing choices", Journal of Consumer Behaviour : An International Research Review, 3(3), pp.251~262 (2004)
- Yamaguchi, Kota, M., "Paper doll parsing: Retrieving similar styles to parse clothing items", Proceedings of the IEEE international conference on computer vision (2013)
- Yamaguchi, Kota, "Retrieving similar styles to parse clothing", IEEE transactions on pattern analysis and machine intelligence, 37(5), pp.1028~1040 (2014)
- Xu, Qi, "Innovative design of intangible cultural heritage elements in fashion design based on interactive evolutionary computation", Mathematical Problems in Engineering 2021, pp.1~11 (2021)
- 이명준, "한국 전통자수를 응용한 현대 패션디자인 연구I", 복식, 57(3), pp.176~190 (2007), 한국복식학회
- Staynov, Stefan, "Traditional Bulgarian Costume Classification in a Tourist Guide application", 2020 International Conference Automatics and Informatics (ICAI), pp.1~4 (2020)
- Liu, Kaixuan, "Research on Chinese traditional opera costume recognition based on improved YOLOv5", Heritage Science, 11(1), pp.1~14 (2023)
- Jiang, Peiyuan, "A Review of Yolo algorithm developments", Procedia Computer Science, 199, pp.1066~1073 (2022)
- Redmon, Joseph, "You only look once: Unified, real-time object detection", Proceedings of the IEEE conference on computer vision and pattern recognition, pp.779~788 (2016)
- "Ultralytics YOLOv8 documentation"[URL]
- "what is YOLOv8? The Ultimate Guide"[URL]
- Padilla, Rafael, "A survey on performance metrics for object-detection algorithms", 2020 international conference on systems, signals and image processing (IWSSIP) (2020), IEEE