A Gesture Based Virtual Mouse

Abstract

Our work delves into the complexities of real-time hand motion interpretation and fingertip recognition to simulate the functionality of a traditional mouse. We have developed a technique in Python that effortlessly translates hand movements into mouse commands. This technique uses the angles between fingers to enable advanced mouse operations by calculating the ratio of the silhouette of the hand to its convex hull. Our methodology has been refined to ensure an intuitive and accurate user experience. However, challenges remain in achieving robustness and accuracy in gesture recognition systems in various scenarios, including variations in lighting, hand orientation, and individual human characteristics. These factors have a significant impact on system performance and reliability. To address these challenges, our approach incorporates sophisticated algorithms and machine learning models designed to adapt to different conditions. Despite these advances, further research and development is essential to improve the reliability and comprehensiveness of gesture recognition technologies. Achieving smooth integration into everyday computing contexts requires continuous improvements to effectively handle different environments and user behaviors. Our work highlights the potential of gesture-based virtual mouse systems to revolutionize the interaction between humans and computers. Continued efforts in this area will pave the way for more inclusive, hygienic, and user-friendly computing experiences, ultimately changing the way we interact with technology in our daily lives.