Gesture Volume Control Using Open CV

Abstract

Modern human-computer interactions 
have developed substantially into the 
creation of hassle-free gesture recognition 
as a human-to-computer communication 
solution. 
Traditional volume control 
requires users to access physical input 
tools 
such as keyboards and mice 
alongside external controllers that might 
be restriction or inconvenient to use. A 
new method presents volume control 
through computer vision techniques which 
detect hand movements to operate the 
system. Volume control functions are 
linked to specific gestures through a 
system that tracks hand positions using 
OpenCV combined with MediaPipe and 
Pycaw technologies. The webcam scans 
the user's hand along with measuring the 
key points of thumb and index fingers to 
make identifications. The volume level 
matches accordingly with the distance 
between thumb-tip and index-tip points. 
Reducing the distance between the hand 
points results in lowering the system 
volume. An extended distance between 
points will result in volume increase.Users can operate the system without 
hands thanks to this system which helps 
both accessibility applications along with 
real-time gesture-based controls. The 
method provides users with an efficient 
volume adjustment system through 
responsive controls that remain easy to 
navigate.