2007 Fiscal Year Final Research Report Summary
A Virtual Training System for Supporting Tactical Skill Improvement in Martial Arts Match
Project/Area Number |
18500744
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Single-year Grants |
Section | 一般 |
Research Field |
Educational technology
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Research Institution | Kinki University |
Principal Investigator |
TANAKA Kazumoto Kinki University, School of Engineering, Associate Professor (60351657)
|
Co-Investigator(Kenkyū-buntansha) |
KUROSE Yoshinobu Kinki University, School of Engineering, Professor (00043802)
TOMINAGA Noriyuki Kinki University, School of Engineering, Associate Professor (50188794)
|
Project Period (FY) |
2006 – 2007
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Keywords | Martial Arts / Match Tactics / Open Skill / Physical Skill / Sequential Pattern Mining / Motion Sequence / Motion Capturing / Virtual Space |
Research Abstract |
(1) Athlete's tactics extraction method The method for extracting the feature motion pattern in the offense and defense process of the martial arts match was developed by using sequential pattern mining. First of all, the offense and defense process is expressed by the tuple of a motion label and a positional label in the motion section. Next, the method extracts motion sequences that have a positive correlation with a successful attack and a negative correlation with a failure attack from the database of the offense and defense process. When we analyzed the attack pattern of two Karate players who had National-Sports-Festival (Koku-Tai) victory experience by using the method, each player's feature attack pattern was able to be extracted and was found to coincide with the opinion of a Karate specialist. Moreover, it was clarified that the successful attacks have a strong correlation with the state immediately before each attack according to extracted patterns from the various athlete's matches (130 matches). This result agrees with teaching in martial arts from old. (2) Virtual training system for skill improvement of well-timed attack We have developed a virtual training system for mastering the timing of successful attack based on the result of the tactics pattern extraction. First of all, we designed state transition rule to move a CG player (opponent player) who could give the timing of successful attack to real player (a trainee). Next, the mechanism that the system evaluates whether a trainee correctly reacted to CG player's state transition was clarified. This became possible because captured trainee's motion and CG player's motion could be compared with the tactics pattern. Six student athletes evaluated the system, and the high appraisal was obtained as an independent training system accordingly.
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Research Products
(8 results)