A Review on Hand Gesture Recognition Using ML and DL Based Techniques

Abstract

This paper aims to present and describe several approaches to hand gesture detection via human- Interaction with a computer Computer-human interaction is a crucial part of the majority of people's day-to-day lives, especially when persons who are dumb or deaf of hearing want to communicate. In these situations, getting their message over to the rest of the world is a challenge. Therefore, these individuals can complete various jobs with ease by making an air gesture with their hands in front of a computer camera, which reads their movements into words or text that other individuals can understand. We have spoken about certain Human-Computer Interaction (HCI) strategies and methodologies that will this study's construction of the hand gesture detection system comprises two significant issues. The detection of hands comes first. Making a sign that can be utilized with only one hand at a time is another issue. This study's objective is to develop a system that can recognize, & understand hand gestures using computer vision while dealing with problematic elements including stance, orientation, position, and scale variability. This system must produce a variety of gestures, including numbers and sign language, for this project to be successful. Before any image processing is done, a webcam image is acquired and analyzed to find a hand motion. In this research, methods based on ML and DL will be used to detect hands.