Survey of Hand Gesture Recognition Systems

Abstract

Recognition of human gestures is an important subject in computer science, especially in computer vision and sign language. It aims at interpreting human gestures by mathematical models. Gestures originate from different parts of the human body, but the most common ones emerge from the hand or face. Gestures recognition is a method to enable computers to understand and interpret the language of the human body in the best way possible and to build a bridge between humans and machines from uncomplicated user interfaces that have been command-line to graphical user interfaces GUI, so far they limit the common input on the keyboard and mouse. In this paper, we have reviewed and analyzed several methods of recognition for hand gestures including, Artificial Neural Networks (ANN), Histogram based feature, a Fuzzy Clustering algorithm, Hidden Markov Model (HMM), Condensation algorithm and Finite-State Machine (FSM).