Sports skill frequency analysis with motion image data
| Autor: | Toshiyuki Maeda, Akiyoshi Wakatani, Masumi Yajima |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Frequency analysis
Similarity (geometry) Computer science business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Frequency data Motion (physics) Postural control Image (mathematics) law.invention law Physical information Computer vision Artificial intelligence Time series business |
| Zdroj: | 2018 International Workshop on Advanced Image Technology (IWAIT). |
| DOI: | 10.1109/iwait.2018.8369656 |
| Popis: | This paper addresses skill frequency analysis with motion image data of volleyball attack. We try to justify a assumption that expert skills have relatively low frequency motions rather than novice skills as the similarity of human postural control. For this purpose we have experiments and analyze sports skills as for frequency of motion using time series motion images of volleyball attacks. In our research, volleyball play is analyzed with motion image data recorded by hi-speed cam-coder, where we do not use physical information such as body skeleton model. Time series data are obtained from the motion image data with four marking points, and analyzed in terms of motion frequency. As the experiment results, we in some content classify expert, middle, and novice skill image using frequency data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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