MPH-YOLO method for isolating the controller hand amidst multiple hands in digital interaction environments

https://doi.org/10.55214/25768484.v9i7.8707

Authors

  • Agustinus Rudatyo Himamunanto Faculty of Computer Science, Dian Nuswantoro University, Semarang, Indonesia, and Department of Informatics, Immanuel Christian University, Yogyakarta, Indonesia.
  • Supriadi Rustad Faculty of Computer Science, Dian Nuswantoro University, Semarang, Indonesia.
  • Mochammad Arief Soeleman Faculty of Computer Science, Dian Nuswantoro University, Semarang, Indonesia.
  • Guruh Fajar Shidik Faculty of Computer Science, Dian Nuswantoro University, Semarang, Indonesia.

Hands play a vital role in human-computer interaction. However, ambiguity arises when multiple hand gestures appear within the same frame, leading to misinterpretation in gesture-controlled systems. This study proposes a hybrid method combining MediaPipe Hands (MPH) and a modified YOLO framework to isolate a single control hand using a visual marker. MPH detects hand landmarks, and YOLO identifies whether the hand contains a marker. Experiments involving 800 test videos showed that the method achieved 97.5% accuracy in correctly identifying the controller hand across various visual conditions. The proposed approach contributes to the robustness and precision of real-time gesture-based control systems.

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How to Cite

Himamunanto, A. R. ., Rustad, S. ., Soeleman, M. A. ., & Shidik, G. F. . (2025). MPH-YOLO method for isolating the controller hand amidst multiple hands in digital interaction environments. Edelweiss Applied Science and Technology, 9(7), 665–675. https://doi.org/10.55214/25768484.v9i7.8707

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Published

2025-07-09