Hand Gesture Virtual Car Driving Simulator

Abstract

The evolution of human-computer interaction (HCI) has led to the emergence of more natural, intuitive methods of control, especially in the domain of gaming. Traditional input devices such as keyboards, mice, and joysticks, though reliable, can limit user immersion and interactivity. This project presents a novel hand gesture-based virtual driving simulator that utilizes Open-CV to detect and interpret real-time hand gestures, thereby offering an innovative and engaging alternative to conventional control mechanisms in driving games. The proposed system employs a standard webcam to capture live video input of the user’s hand gestures. Using a combination of computer vision techniques such as contour analysis and convex hull algorithms the system accurately identifies gestures corresponding to steering, acceleration, and braking. These recognized gestures are then mapped to simulated keyboard events, enabling control of a wide range of commercially available driving games. By eliminating the need for additional hardware, the system offers an affordable and accessible solution for enhancing user experience. Experimental results demonstrate the system’s efficiency, achieving over 90% accuracy in gesture recognition and maintaining a response latency under 100 milliseconds, thereby ensuring smooth gameplay. The system was successfully tested with multiple racing simulators, receiving positive feedback from users who appreciated its intuitive and immersive nature. This project not only showcases the potential of vision-based gesture recognition in gaming but also sets a foundation for future enhancements involving complex gesture sets and virtual reality (VR) integration.