DEEP LEARNING FOR TWO-PERSON MAE MAI MUAY THAI CLASSIFICATION: LEVERAGING NORMALIZED HUMAN POSE SEQUENCES AND CNN-LSTM.
Muay Thai postures are the distinctive stances and movements used in traditional Thai boxing, concentrating on balance, strength, and fluid transitions between offensive and defensive techniques. Therefore, this study presents a novel system for detecting and categorizing Muay Thai postures through...
| Publicado en: | Scientific Culture Vol. 11; no. 4; pp. 333 - 350 |
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| Autores principales: | , |
| Formato: | Artículo |
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University of the Aegean
2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=191047123&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 191047123 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 24080071 I6HU jtl: Scientific Culture issn: 24080071 maglogo: N pubinfo: dt: 2025 vid: 11 iid: 4 pid: 47715 pub: University of the Aegean artinfo: ui: 191047123 10.5281/zenodo.11042528 ppf: 333 ppct: 17 formats: tig: atl: DEEP LEARNING FOR TWO-PERSON MAE MAI MUAY THAI CLASSIFICATION: LEVERAGING NORMALIZED HUMAN POSE SEQUENCES AND CNN-LSTM. aug: au: Yoddamnern, Thanirat Riyamongkol, Panomkhawn affil: Faculty of Engineering, Naresuan University, Phitsanulok, Thailand su: Deep learning Combat sports Motion analysis Video processing Long short-term memory Sports sciences Human activity recognition sug: subj: Deep learning Combat sports Motion analysis Video processing Long short-term memory Sports sciences Human activity recognition keyword: Action Recognition CNN-LSTM Human Pose Estimation Joint Detection Muay Thai Posture ab: Muay Thai postures are the distinctive stances and movements used in traditional Thai boxing, concentrating on balance, strength, and fluid transitions between offensive and defensive techniques. Therefore, this study presents a novel system for detecting and categorizing Muay Thai postures through video processing and deep learning methods, which are skilled at examining the coordinated movements of two people fighting on the stage. The procedure involves identifying human formations and evaluating incorporated positions during duplicative movements, and organizing the postures operating a hybrid CNN and LSTM model. Moreover, to improve learning efficiency with joint position sequence data, the MinMaxScaler technique is used for data normalization. The type is based on an extensive dataset of 590 videos featuring various backgrounds, divided into 80% for training and 20% for testing. The resulting model completes an overall type accuracy of 84%, providing a strong basis for future applications in solely and paired of Muay Thai analysis. This approach offers potential advantages in sports science, competitor training, and motion analysis, allowing real-time posture recognition and performance evaluation. It helps coaches and practitioners identify incorrect techniques, reduce injury risks, and increase the accuracy of battle movements. In addition, future developments could include real-time integration into training applications, support for 3D pose analysis, and expanded datasets to improve the model's accuracy and validity across various conditions and practitioners. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2025 holdings: @attributes: islocal: N |
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