Intelligent Approaches to interact with Machines using Hand Gesture Recognition in Natural way: A Survey

TL;DR

This survey reviews intelligent hand gesture recognition methods that enable natural human-machine interaction without extra devices, focusing on soft computing techniques and image preprocessing methods.

Contribution

It provides a comprehensive overview of recent intelligent approaches in hand gesture recognition, emphasizing soft computing methods and image processing techniques.

Findings

Neural networks and fuzzy logic are commonly used in gesture recognition.

Preprocessing techniques like segmentation and hand image construction are crucial.

Comparison of different methods highlights the effectiveness of various approaches.

Abstract

Hand gestures recognition (HGR) is one of the main areas of research for the engineers, scientists and bioinformatics. HGR is the natural way of Human Machine interaction and today many researchers in the academia and industry are working on different application to make interactions more easy, natural and convenient without wearing any extra device. HGR can be applied from games control to vision enabled robot control, from virtual reality to smart home systems. In this paper we are discussing work done in the area of hand gesture recognition where focus is on the intelligent approaches including soft computing based methods like artificial neural network, fuzzy logic, genetic algorithms etc. The methods in the preprocessing of image for segmentation and hand image construction also taken into study. Most researchers used fingertips for hand detection in appearance based modeling. Finally the comparison of results given by different researchers is also presented.