Real Time Gesture Recognition Using Gaussian Mixture Model
Aisha Meethian · 2013
This paper investigates a real time gesture recognition system which recognizes sign language in real time manner on a laptop with webcam. Real time performance is achieved by using combination of Euclidistance based hand tracking and mixture of Gaussian for background elimination. In this paper gesture reorganization is proposed by using neural network and tracking to convert the sign language to voice/text format. The aim of research to develop a Gesture Recognition Hand Tracking (GR-HT) system for hearing impaired community. The experimental result shows that the proposed GR-HT system achieves satisfactory performance in hand gesture recognition.