TECHNIQUES FOR ONLINE GESTURE RECOGNITION ON WORKSTATIONS

We describe an automatic, unsupervised procedure for the recognition o f a small set of gestures drawn with the aid of a mouse in the Windows environment of a modern computer workstation. The paper considers the application to various shorthand gestures which are commonly used in the design of computer networks. Furthermore, the method incorporates a facility for automatic addition of new gestures and the deletion of unnecessary gestures so that the approach may be easily adapted to oth er sets of gestures. The proposed procedure utilizes certain character istic shape features extracted from each gesture together with appropr iate decision rules. This is backed up by a menu-based correction/conf irmation utility. The problem is of particular interest since the gest ures are subject to considerable internal rescaling and changes in ori entation because of both the individual's drawing style and the nature of the application. The characteristic features are primitives chosen by inspection of the geometrical properties of the expected shapes ba cked up with a video-recorded psychological study of drawing style. We present some experimental results for a specific set of 'network desi gn gestures' which indicate the potential for accurate gesture recogni tion.