Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)

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Hand Gesture Recognition and Volume Control

Authors
R. Tamilkodi1, 2, N. Madhuri1, 2, *, G. Dhanushkumar1, 2, G. Dileepkumar1, 2, G. Rajkumar1, 2, Y. Sandeep1, 2
1Professor Department of Computer Science & Engineering (AIML & CS) Godavari Institute of Engineering & Technology, Rajahmundry, Andhra Pradesh, India
2Assistant Professor Department of Computer Science & Engineering (AIML & CS) Godavari Institute of Engineering & Technology, Rajahmundry, Andhra Pradesh, India
*Corresponding author. Email: nmadhuri@giet.ac.in
Corresponding Author
N. Madhuri
Available Online 30 July 2024.
DOI
10.2991/978-94-6463-471-6_96How to use a DOI?
Keywords
Gesture recognition; accessibility; communication; Volume control; hand tracking
Abstract

The technology of identifying movements in real-time video is called “motion recognition”. These actions are classified according to the properties they represent. Creating awareness of movements is a difficult task because it overcomes two major challenges. The first challenge was to enable control of movement, allowing users to effectively interact with computers or other devices using only one hand. This technology has many applications, especially in human-computer interaction and linguistic tasks. Simple techniques such as hand classification and measurement using Haar cascade classifiers in Python and OpenCV can be used to generate gesture recognition. This article focuses on gesture recognition as a qualitative analysis. This setup includes a camera that captures the user's movements, which are then processed by the system. The main purpose of gesture recognition is to develop awareness and use human movements to control devices and communicate. Live gesture recognition allows users to work with the front camera on their computers, providing greater interaction and understanding with the technology. We will create an orientation with the help of the OpenCV module which can control the system with gestures without using a keyboard or mouse.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
Series
Advances in Computer Science Research
Publication Date
30 July 2024
ISBN
978-94-6463-471-6
ISSN
2352-538X
DOI
10.2991/978-94-6463-471-6_96How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - R. Tamilkodi
AU  - N. Madhuri
AU  - G. Dhanushkumar
AU  - G. Dileepkumar
AU  - G. Rajkumar
AU  - Y. Sandeep
PY  - 2024
DA  - 2024/07/30
TI  - Hand Gesture Recognition and Volume Control
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 1002
EP  - 1012
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_96
DO  - 10.2991/978-94-6463-471-6_96
ID  - Tamilkodi2024
ER  -