Animation of hand motion from target posture images using an anatomy-basedhierarchical model

This paper presents an anatomy-based hierarchical approach for modelling th e human hand and animating hand gesture. The resulting technique greatly si mplifies the motion data acquisition and the process of motion analysis and synthesis. Key contributions of our approach include (1) no high-speed mot ion tracker is needed as the technique is able to generate and animate anat omically realistic intermediate motion or in-betweens from only the startin g and the final static postures of hand gestures; (2) the interpolated post ures generated by the synthetic hand model are anatomically realistic; and (3) a gesture database can be easily built incrementally and automatically. The use of model hierarchy abstracts the underlying representations and co mputations, which allows the hand motion to be specified using high-level b ehavioural descriptions. In this work, we also propose a hand action coding system (HACS) to codify hand gestures in terms of hand muscle activation c ommands. The anatomy-based model, together with the HACS, allows complex se quence of hand gestures to be animated using high-level textual scripts or from static images of the target hand gestures to be animated. As a by-prod uct, the anatomical-based hand model can potentially be applied to inferrin g which muscle or group of muscles are involved in a given hand gesture. (C ) 2001 Elsevier Science Ltd. All rights reserved.