A HMM-based system for real-time gesture recognition in movie sequences

Abstract

In the paper there is presented an efficient system for dynamic gesture recognition in movie sequences based on hidden Markov models. The system uses colour-based image segmentation methods and introduces high-dimensional feature vectors to more accurately describe hand shape in the picture. It also utilizes a-priori knowledge on gestures construction in order to allow effective dimensionality reduction, hand posture classification and detection schemes. The system has demonstrated a reliable recognition properties both for static hand postures and dynamic gestures in movie sequences.