MPH-YOLO method for isolating the controller hand amidst multiple hands in digital interaction environments - Himamunanto, Agustinus Rudatyo; Rustad, Supriadi; Soeleman, Mochammad Arief; Shidik, Guruh Fajar (Edelweiss Applied Science and Technology, 2025)
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.