Summary: | 碩士 === 國立清華大學 === 資訊工程學系所 === 107 === The population of playing baseball/softball worldwide is quite large. In baseball/softball, batting is a fundamental action, but it is also one of the most difficult skills to master. Batting requires constant practice and proper guidance. Experienced coaches can provide instant diagnoses and feedback tailored for individual players, whereby shortening the learning curve. Unfortunately, not every player can have an experienced coach by the side. Past efforts on coaching tools for sports are either too expensive and awkward to use, or too limited to provide useful diagnosis and guidance. In this thesis, we introduce a low-cost diagnosis and guidance tool for batting practice in baseball/softball. The tool requires only one wearable device and one camera, such as the one on the smartphone, to capture the player's motion. The collected data are analyzed to derive the features of the player's actions in different swing stages, which are then compared with the reference actions to detect possible mistakes and provide suitable guidance to the player. We have collected about 1200 swing motions from four experts and eight novice players. The evaluation results from our tool are compared with those from the experienced coach. The experiments show that our tool can achieve about 80% accuracy in terms of diagnosis and guidance.
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