Intelligent Approaches to interact with Machines using Hand Gesture Recognition in Natural way: A Survey
It addresses the problem of enabling natural human-machine interaction without extra devices for applications such as robotics and virtual reality, but is incremental as a survey.
This survey paper reviews intelligent approaches for hand gesture recognition, focusing on soft computing methods like neural networks and fuzzy logic, and compares results from various researchers.
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.