Artificial Intelligence (AI) has significantly transformed human-computer interaction, with gesture and vision-based systems offering a new dimension of accessibility and efficiency. The AI Virtual Mouse utilizes computer vision and machine learning algorithms to enable cursor control, click, and scrolling actions through real-time hand gesture recognition using a standard webcam. This innovation eliminates the dependence on physical devices such as traditional mice, thereby enhancing hygiene, convenience, and inclusivity for users with mobility impairments. By employing algorithms such as Convolutional Neural Networks (CNN), MediaPipe Hand Tracking, and Support Vector Machines (SVM), the system achieves high accuracy and responsiveness across diverse environmental conditions. The proposed model further integrates evaluation metrics such as Confusion Matrix, Precision, Recall, F1-Score, and Accuracy to validate performance. Experimental outcomes demonstrate an accuracy of up to 99%, proving the robustness and reliability of the AI-based system. This project emphasizes the potential of intelligent, vision-driven interfaces to revolutionize interaction design and promote seamless, contactless computing experiences..
In summary, the development of the proposed AI Virtual Mouse system underscores a meaningful shift in human-computer interaction by replacing traditional physical input devices with a gesture- and vision-based interface. Integrating hand-tracking and gesture-recognition technologies (for example, using frameworks like MediaPipe and OpenCV) allows users to control cursors, perform clicks, drags, and scrolls without touching a mouse. Numerous recent research works demonstrate the viability of such systems: one study achieved ~96% recognition accuracy for gesture-based cursor control. IJIREEICE+2irjaeh.com+2
The proposed system offers several significant advantages: enhanced accessibility for users with mobility impairments, hygiene improvement by minimizing surface contact, cost-effectiveness by relying on an ordinary webcam instead of specialized hardware, and a more intuitive, natural interface that aligns with modern interaction patterns. By setting concrete computational benchmarksβsuch as β₯ 25β30 fps frame rate, latency under ~50β100 ms, and gesture accuracy above 95%βthis project aims to produce a responsive real-world solution rather than merely a research prototype. Nevertheless, the work also acknowledges key challenges and limitations: variability in lighting and background conditions, gesture ambiguity or mis-interpretation, hardware differences across users, fatigue from extended hand gestures, and the need for smooth user feedback and calibration. Furthermore, integrating the system seamlessly into existing operating systems and applications, while maintaining low cost and high reliability, remains a demanding task.Ultimately, the AI Virtual Mouse represents a forward-looking contribution to human-computer interaction. It bridges the gap between cutting-edge gesture-recognition research and practical usability in everyday computing. The successful implementation and evaluation of this system will open doors to broader applications, including assistive technologies, smart environments, virtual/augmented reality interfaces, and more hygienic public computing settings.
References
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ARUN KUMAR V, ALAMELU MANGAI M (2026). SMART CASH TERMINAL USING EMBEDDED SYSTEMS FOR AUTOMATED PAYMENT PROCESSING.. International Journal of Computer Science Engineering Techniques, 10(6), 421β427. ISSN: 2455-135X. DOI: https://doi.org/10.5281/zenodo.24136812