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Real-time Hand Gesture Pattern Recognition and Device Control through Inbuilt Webcam

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Link to refer to this document:
10.3311/WINS2023-002
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  • 1st Workshop on Intelligent Infocommunication Networks, Systems and Services [19]
Abstract
Home automation technique is used to design and implement a remotely controlled, energy efficient and highly scalable Smart Home with basic features that safeguard the resident’s comfort and security. Controlling electric home appliances and gadgets with the help of switches is difficult for old and disabled people. The basic problems faced by disabled people in day-to-day life in their homes is to turn ON or OFF the daily used equipment like lights, fans and difficulty in analyzing switches are observed many times. In this paper, we attempt to propose a real-time hand gesture-based recognition system using a simple webcam and a microcontroller that can automate the control of electrical home appliances using simple hand gestures without using multiple sensors or any kind of special equipment. The proof of concept is demonstrated by controlling a set of different colored electric bulbs that represent the appliances or switches, which are further connected to an Arduino Uno Microcontroller, which in turn is connected to the personal computer where the gesture recognition is implemented with the help of real-time optimized computer vision library.
Title
Real-time Hand Gesture Pattern Recognition and Device Control through Inbuilt Webcam
Author
Zargar, Hisham
Shah, Laraiba
Date of issue
2023
Access level
Open access
Copyright owner
Szerző
Conference title
1st Workshop on Intelligent Infocommunication Networks, Systems and Services (WI2NS2)
Conference place
Budapest
Conference date
2023.02.07
Language
en
Page
7 - 11
Subject
computer vision, hand gesture, pattern recognition, home automation, machine learning
Version
Post print
Identifiers
DOI: 10.3311/WINS2023-002
Title of the container document
1st Workshop on Intelligent Infocommunication Networks, Systems and Services
ISBN, e-ISBN
978-963-421-902-6
Document type
Konferenciaközlemény
Document genre
Konferenciacikk
University
Budapest University of Technology and Economics
Faculty
Faculty of Electrical Engineering and Informatics

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DSpace software copyright © 2002-2016  DuraSpace
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