This paper presents AirClick, an AI-based virtual mouse system that enables users to control desktop operations through real-time hand and face gestures using a standard webcam. The system addresses limitations of traditional input devices in situations requiring touchless interaction, accessibility support, and natural human–computer interaction. The proposed framework integrates OpenCV for image processing, MediaPipe for hand and face landmark detection, and Python-based automation to translate gestures into cursor movements and mouse actions. The system supports cursor navigation, left click, right click, double click, scrolling, drag-based selection, gesture-based mode switching, and pause or resume functionality. A user profile mechanism stores face images and sensitivity preferences so returning users can automatically load their settings. Experimental observations indicate that the system provides smooth real-time interaction under normal lighting conditions and performs effectively as a low-cost academic prototype. The study demonstrates that multimodal gesture control can serve as a practical alternative to a physical mouse for research, education, and assistive computing environments.
Londhe et al. (Thu,) studied this question.