Detection of Traditional Costumes: A Computer Vision Approach

• 영문명: Detection of Traditional Costumes: A Computer Vision Approach
• 발행기관: 한국스마트미디어학회
• 저자명: Marwa Chacha Andrea Mi Jin Noh Choong Kwon Lee
• 간행물 정보: 『스마트미디어저널』Vol12, No.11, 125~133쪽, 전체 9쪽
• 주제분류: 공학 > 컴퓨터학
• 파일형태: PDF
• 발행일자: 2023.12.31

영문 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.

목차

Ⅰ. INTRODUCTION

Ⅱ. RELATED WORK

Ⅲ. PROPOSED METHODOLOGY

Ⅳ. RESULTS

Ⅴ. CONCLUSIONS

REFERENCES

키워드

Traditional costume YOLOv8 Computer Vision Object detection Fashion