Hand Gesture Recognizer

Author(s)	Ms. SWATHI KUMARI, Mr. ALOK SINGH KUSHWAHA, Ms. SUNIDHI SINGH, Mr. REDDYPALLY SAIKOMAL, Mr. AGRAWAL PRATHMESH KISHOR
Country	India
Abstract	This paper presents the design and implementation of a vision-based hand gesture recognition system combined with voice control for human-computer interaction (HCI). The system uses MediaPipe for real-time hand tracking and OpenCV for image processing, translating gestures into cursor movements and clicks through PyAutoGUI. Additionally, a SpeechRecognition-based voice module interprets spoken commands for actions such as opening applications and retrieving online data. The hybrid online/offline architecture ensures reliability, low latency (0.04s), and high accuracy (96.4%) while maintaining user privacy. This work demonstrates an accessible and efficient interaction model suitable for assistive technologies, smart homes, and sterile environments.
Keywords	Hand Gesture Recognition, Human-Computer Interaction, MediaPipe, OpenCV, Voice Command, Artificial Intelligence, Machine Learning, Accessibility, Multi-Modal System
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 4, October-December 2025
Published On	2025-10-29
DOI	https://doi.org/10.71097/IJSAT.v16.i4.8829
Short DOI	https://doi.org/g98ndf

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International Journal on Science and Technology