HAND TRAJECTORY BASED GESTURE RECOGNITION USING SELF-ORGANIZING FEATURE MAPS AND MARKOV MODELS

Abstract

This work presents the design and experimental verification of an original system architecture aiming at recognizing gestures based solely on the hand trajectory. Self organizing feature maps are used to model spatial information while Markov models encode the temporal aspect of hand position within a trajectory. A validated classification mechanism is produced through a set of models and a committee machine setup ensures robustness as indicated by the experimental results performed. Index Terms—gesture recognition, self organizing feature map, Markov processes 1