Comparison of hand segmentation methodologies for hand gesture recognition

Abstract

The Hand gesture has provided significant means of communication in human daily interaction and has been widely explored in the Human-Computer Interaction (HCI) studies. This paper presents a comparison of hand segmentation methodologies in the early stage development of an appearance-based hand gesture recognition system for sign language application. The hand segmentation method is based on Jones and Rehg generic skin color model and frame differencing technique that utilized the color and motion cues of image content. Several issues and challenges occurred during the experiments are also discussed and later tackled by the current approach. The present approach applied the idea of integrating both color and motion cues into a single probability map and yield robust features for further tasks. It is merely a first step progress towards an independent environment and signer for the hand gesture recognition system.