• Suganya S
• Krishna veerandhra suthir S
• Mohan raj S
• Selva mani S

Abstract— A virtual mouse system records the user's hand motions with a camera. Sophisticated algorithms then analyze the recorded hand gestures to identify hand movements that are particular to mouse actions including clicking, double-clicking, dragging, and scrolling. This procedure makes use of OpenCV and MediaPipe, a state-of-the-art machine learning framework with exceptional real-time hand gesture recognition capabilities. The efficiency of the system depends on MediaPipe's capacity to distinguish between various hand gestures and facial expressions with accuracy. This allows the system to function flawlessly in a range of environments and lighting circumstances. The system utilizes AutoPy, a powerful toolkit made to mimic conventional mouse inputs, after identifying a hand motion. To do this, the identified hand gestures must be translated into exact mouse clicks and cursor movements on the computer.

OpenCV, MediaPipe, system, mouse, hand, simulating

"HAND GESTURE RECOGNITION FOR VIRTUAL MOUSE CONTROL USING MEDIAPIPE IN ARTIFICIAL INTELLIGENCE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.e438-e443, May-2024, Available :http://www.jetir.org/papers/JETIR2405450.pdf

"HAND GESTURE RECOGNITION FOR VIRTUAL MOUSE CONTROL USING MEDIAPIPE IN ARTIFICIAL INTELLIGENCE", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppe438-e443, May-2024, Available at : http://www.jetir.org/papers/JETIR2405450.pdf