Hand Gesture Desktop Control with Python

With the rapid progress of technology, traditional presenting styles sometimes fail to engage audiences effectively. The search for new ways to improve user engagement has been spurred by the growing need for interactive and user-friendly presentation technologies. To create an interactive presentation system, this project makes use of computer vision and hand gesture detection. The system records live video input from a webcam and process it using OpenCV for image processing and the CvZone library for hand tracking, enabling smooth slide navigation and annotation. The main goal for this is to create a user interface that is controlled through hand gestures, which would allow speakers to control their slide presentations. This not only helps with how session agendas are managed, but it also provides a better experience for the audience. In addition, the system eliminates the need for traditional input devices like keyboards and remotes making it a more user-friendly and intuitive way to control presentations. The idea for this project originates from the necessity to improve communication quality under different conditions (for instance, for educational purposes or business dives), with the intention that interactive presentations can adequately enhance people not only learning and understanding but also their involvement in audience life. By combining real-time video processing with the ability to track hand movements, we aim to provide a novel way of interacting in space that is both dynamic and user-oriented.