A Study on Analysis and Visualization of Goodness for the Transmission of Local Performing Arts

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K03152
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 09070:Educational technology-related
• Research Institution: Iwate Prefectural University
• Principal Investigator: Matsuda Koichi 岩手県立大学, ソフトウェア情報学部, 准教授 (70325926)
• Co-Investigator(Kenkyū-buntansha): PRIMA・OKY・ DICKY 岩手県立大学, ソフトウェア情報学部, 教授 (20344624)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 郷土芸能 / モーションセンサ / 高速撮影カメラ

Outline of Final Research Achievements

In this study, we explored a methodology for analyzing and visualizing skill in individuals and groups. For the "individual" case, the softness of the arm movements was considered. It was unknown under what conditions the numerical impression of the time difference in the onset of movement between joints and the transition of angular change would change. Therefore, we computationally generated a comprehensive set of motion data of various movements and analyzed the relationship between the numerical values and the factors that contribute to the impression. For the "group," we referred to how the evaluator observes the goodness of the group as a whole. Nine performers were lined up in a motion-captured group, and the number of seconds in which they felt displacement and the effect of the way they were lined up on their evaluation were investigated.

Free Research Field

身体知

Academic Significance and Societal Importance of the Research Achievements

熟練者の動作の分析は先行研究で多々行われてきているが，人間から取得するデータを対象としているため，網羅的に分析することができなかった．本研究では，熟練者の動作・判断要素をモデル化し，数値的に操作することにより，網羅的にパターンを作成し，評価するアプローチ方法を開発した．これにより，人間では取得できなかったさまざまなパターンに対する評価が可能となり，また，将来的には，人間の動作をモデルに当てはめることにより，個性を反映したモーションデータ生成への応用が期待できる．