A Dynamic Gesture and Posture Recognition System

This paper presents a real time dynamic hand gesture and posture recognition system based on a neural network and a Hidden Markov Model. For skin color segmentation an adaptive online trained skin color model is used, while the hand posture recognition is accomplished through a likelihood-based classification technique of geometric features. A novel trajectory smoothing technique based on Self Organized Neural Network is introduced to improve HMM classification performance of dynamic gestures. The aim of the proposed system is the creation of a visual dictionary combining hand postures and dynamic gestures. The system has been successfully tested with many people under varying light conditions and different web cameras.