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AI-Powered Virtual Mouse Control Through Hand Gestures With Computer Vision
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Author(s): Arjun Paramarthalingam (University College of Engineering, Villupuram, India), Ashokkumar Janarthanan (University College of Engineering, Villupuram, India), Amirthasaravanan Arivunambi (SRM Institute of Science and Technology, Kattankulathur, India), Srinivas Saravanan Ariyangavu (University College of Engineering, Villupuram, India), Hariprasath Senthamaraikannan (University College of Engineering, Villupuram, India)and Rekha Ganapathy (SRM Institute of Science and Technology, Kattankulathur, India)
Copyright: 2025
Pages: 16
Source title:
Harnessing AI in Geospatial Technology for Environmental Monitoring and Management
Source Author(s)/Editor(s): Froilan D. Mobo (Philippine Merchant Marine Academy, Philippines)
DOI: 10.4018/979-8-3693-8104-5.ch003
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Abstract
This article introduces an Artificial Intelligence (AI) enabled virtual mouse system that utilizes hand gestures and fingertip detection to operate computer mouse functions through AI and computer vision techniques. It serves as a convenient alternative to traditional physical mouse, offering users increased flexibility and accessibility in navigating and controlling their devices. In this article, the proposed work uses three modules such as OpenCV, MediaPipe and PyautoGUI to create the virtual mouse system. OpenCV library is used for its real-time computer vision functionality to help us to capture the hand using the web camera. The MediaPipe framework is used to detect the hand region using KLT Tracking Algorithm and then the K-cosine border tracking algorithm is used to identify various types of hand gesture movements to mimic the computer mouse cursor movement and scrolling operations. The PyAutoGUI module is used to perform appropriate mouse actions based on the recognized hand gestures.
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