VREN: Volleyball Rally Dataset with Expression Notation Language

Xia, Haotian; Tracy, Rhys; Zhao, Yun; Fraisse, Erwan; Wang, Yuan-Fang; Petzold, Linda R.

doi:10.1109/ickg55886.2022.00050

Cited by 3 publications

(1 citation statement)

References 26 publications

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“…Pelaksanaan pada permainan bola voli diawali dengan servis yang merupakan salah satu teknik untuk memulai permainan (Casimiro-Artés et al, 2023;Xia et al, 2022). Dalam servis bawah, pemain meletakkan bola di depan atau sedikit di atas kaki servis, kemudian memukul bola dengan tangan terbuka atau tangan tertutup ke arah lapangan lawan (Gani et al, 2022).…”

Section: Pendahuluanunclassified

Peningkatan hasil belajar servis bawah bola voli melalui media pembelajaran audio-visual

Marsuna

2023

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Masalah: Apakah melalui media pembelajaran audio visual dapat meningkatkan hasil belajar servis bawah bola voli. Tujuan: untuk mengatahui peningkatan hasil belajar servis bawah permainan bola voli melalui media pembelajaran audio-visual. Metode: Jenis penelitian yaitu penelitian tindakan kelas yang dilaksanakan dengan 2 siklus yaitu dengan tahapan perencanaan, pelaksanaan, pengamatan dan tindakan. Subyek yaitu siswa SMA Negeri 3 Konawe Selatan yang berjumlah 30 orang. Teknik pengumpulan data dilakukan dengan observasi dan tes hasil belajar siswa pada masing-masing siklus. Hasil: Hasil penelitian dari observasi siswa siklus I mencapai 70% dan meningkat pada siklus II menjadi 90%, dan hasil observasi guru pada siklus I mencapai 70% dan meningkat pada siklus ke II menjadi 100%, sedangkan untuk hasil belajar siswa siklus I mencapai 66,67% dan meningkat menjadi 93,33% pada siklus II. Kesimpulan: Dari hasil penelitian tindakan kelas dapat disimpulkan bahwa pembelajaran dengan menggunakan media audio-visual dapat meningkatkan hasil belajar servis bawah permainan bola voli.

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Section: Pendahuluanunclassified

Peningkatan hasil belajar servis bawah bola voli melalui media pembelajaran audio-visual

Marsuna

2023

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Advanced Volleyball Stats for All Levels: Automatic Setting Tactic Detection and Classification with a Single Camera

Xia,

Tracy,

Zhao

et al. 2023

2023 IEEE International Conference on Data Mining Workshops (ICDMW)

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Cross-modal self-attention mechanism for controlling robot volleyball motion

Wang,

Liang

2023

Front. Neurorobot.

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IntroductionThe emergence of cross-modal perception and deep learning technologies has had a profound impact on modern robotics. This study focuses on the application of these technologies in the field of robot control, specifically in the context of volleyball tasks. The primary objective is to achieve precise control of robots in volleyball tasks by effectively integrating information from different sensors using a cross-modal self-attention mechanism.MethodsOur approach involves the utilization of a cross-modal self-attention mechanism to integrate information from various sensors, providing robots with a more comprehensive scene perception in volleyball scenarios. To enhance the diversity and practicality of robot training, we employ Generative Adversarial Networks (GANs) to synthesize realistic volleyball scenarios. Furthermore, we leverage transfer learning to incorporate knowledge from other sports datasets, enriching the process of skill acquisition for robots.ResultsTo validate the feasibility of our approach, we conducted experiments where we simulated robot volleyball scenarios using multiple volleyball-related datasets. We measured various quantitative metrics, including accuracy, recall, precision, and F1 score. The experimental results indicate a significant enhancement in the performance of our approach in robot volleyball tasks.DiscussionThe outcomes of this study offer valuable insights into the application of multi-modal perception and deep learning in the field of sports robotics. By effectively integrating information from different sensors and incorporating synthetic data through GANs and transfer learning, our approach demonstrates improved robot performance in volleyball tasks. These findings not only advance the field of robotics but also open up new possibilities for human-robot collaboration in sports and athletic performance improvement. This research paves the way for further exploration of advanced technologies in sports robotics, benefiting both the scientific community and athletes seeking performance enhancement through robotic assistance.

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VREN: Volleyball Rally Dataset with Expression Notation Language

Cited by 3 publications

References 26 publications

Peningkatan hasil belajar servis bawah bola voli melalui media pembelajaran audio-visual

Peningkatan hasil belajar servis bawah bola voli melalui media pembelajaran audio-visual

Advanced Volleyball Stats for All Levels: Automatic Setting Tactic Detection and Classification with a Single Camera

Cross-modal self-attention mechanism for controlling robot volleyball motion

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