Computer vision-based visualization and quantification of body skeletal movements for investigation of traditional skills: the production of Kizumi winnowing baskets
| Autor: | Peng Yang, Yuka Furukawa, Migiwa Imaishi, Mitsunori Kubo, Akira Ueda |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: |
Body skeletal movement
Simplification Visualization Farming tool Wrist trajectory Technology Mechanical engineering and machinery TJ1-1570 Control engineering systems. Automatic machinery (General) TJ212-225 Machine design and drawing TJ227-240 Technology (General) T1-995 Industrial engineering. Management engineering T55.4-60.8 Automation T59.5 Information technology T58.5-58.64 |
| Zdroj: | ROBOMECH Journal, Vol 11, Iss 1, Pp 1-9 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2197-4225 |
| DOI: | 10.1186/s40648-024-00280-4 |
| Popis: | Abstract This paper explores the application of computer vision and mathematical modeling to analyze the intricate movements involved in weaving a traditional farming tool, the winnowing basket. By utilizing OpenPose algorithms, the study simplifies and visualizes the craftsmen's motions, particularly focusing on wrist movements. Video data of craftsmen in Chiba, Japan, creating Kizumi (place name) winnowing baskets is used as the basis for analysis. The extracted information is used to generate 2D motion trajectories of the wrist, allowing a comparison between beginners who watched parsed videos and those who watched the original videos in terms of skill acquisition and learning time. By visualizing human body behavior and combining statistical results, this study demonstrates the potential of artificial intelligence techniques such as computer vision for observing repetitive human movement and inheriting traditional skills. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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