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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Jensen, U. Eskofier, B. Dassler, F. |
| Copyright Year | 2012 |
| Description | Author affiliation: Digital Sports Group, Pattern Recognition Lab, University of Erlangen-Nuremberg, Germany (Jensen, U.; Eskofier, B.) || Adidas Group, Herzogenaurach, Germany (Dassler, F.) |
| Abstract | The complex movement sequences of golf require supporting tools for players and coaches alike. We developed a system that classifies the experience level and trained it with data from an inertial sensor on the club head. Based on 315 golf putts from eleven subjects the system differentiated between experienced and unexperienced players with a classification rate of 86.1%. To improve the classification system and obtain discriminant features we additionally integrated a feature selection step. We compared different selection approaches and concluded that a leave-subject-out feature selection was the appropriate approach to predict the true performance of a live system. The selected features can be fed back to coaches and help them to guide players to a better putting technique. |
| Starting Page | 1735 |
| Ending Page | 1738 |
| File Size | 1030019 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467322164 |
| ISSN | 10514651 |
| e-ISBN | 9784990644109 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-11-11 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | ICPR Org Committee |
| Subject Keyword | Training Kinematics Pattern recognition Mobile communication Niobium Feature extraction Sports equipment |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition |
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