Gesture Master: Gesture-Controlled Gaming System Through Hand Detection Using OpenCV, Pygame, and Mediapipe for Real-Time Interaction
摘要
Gaming development over the years has been marked by rapid advancements and shifts in design, gameplay and accessibility. One of the innovative developments in the gaming industry is the integration of Artificial intelligence. More advancements such as Gesture controlled gaming use of hand detections that enhances user experience, integration of Cutting-edge technologies and innovation in game control mechanisms. Problems arise in traditional gaming methods that use manual inputs like controllers, keyboards, keys, etc. These may lead to the limitations in the interactive gaming experience for the users. To overcome and mitigate the drawbacks, cutting-edge technologies like Artificial Intelligence, Computer vision, Deep learning models like Convolutional Neural Networks can be implemented to enhance the gaming experience with real-time interaction. The proposed system is centered on identifying specific hand gestures to interpret the actions in the game. Gamers can control the gameplay actions using natural hand movements. To be specific Mediapipe, OpenCV is used for capturing and processing hand detection with gesture recognition. In addition, Pygame will be used to develop the basic Flappy bird game to integrate the gesture control. Thus, real-time interaction in gaming through gestures will create a responsive and innovative environment.