Hand gesture recognition using machine learning algorithms

Authors

  • Abhishek B BMS Institute of Technology, Bangalore
  • Kanya Krishi BMS Institute of Technology, Bangalore
  • Meghana M BMS Institute of Technology, Bangalore
  • Mohammed Daaniyaal BMS Institute of Technology, Bangalore
  • Anupama H S BMS Institute of Technology, Bangalore

DOI:

https://doi.org/10.11591/csit.v1i3.pp116-120

Keywords:

Gesture recognition, Human–computer interaction, User-friendly interface

Abstract

Gesture recognition is an emerging topic in today’s technologies. The main focus of this is to recognize the human gestures using mathematical algorithms for human computer interaction. Only a few modes of human-computer interaction exist, they are: through keyboard, mouse, touch screens etc. Each of these devices has their own limitations when it comes to adapting more versatile hardware in computers. Gesture recognition is one of the essential techniques to build user-friendly interfaces. Usually, gestures can be originated from any bodily motion or state, but commonly originate from the face or hand. Gesture recognition enables users to interact with the devices without physically touching them. This paper describes how hand gestures are trained to perform certain actions like switching pages, scrolling up or down in a page.

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Published

2020-11-01

How to Cite

[1]
A. B, K. Krishi, M. M, M. Daaniyaal, and A. H S, “Hand gesture recognition using machine learning algorithms”, Comput Sci Inf Technol, vol. 1, no. 3, pp. 116–120, Nov. 2020.

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