Hand gesture animation from static postures using an anatomy-based model

Automatic interpretation and animation of human motion has become an important research topic among researchers in virtual reality and computer animation. One major problem encountered during hand motion analysis is the large amount of data that need to be captured and analyzed. Even for a human hand, although only a small part of the body is involved, there are about 30 motion parameters for each hand posture. The authors present an approach to hand motion animation using only static images of the set of target gestures. We achieve naturalistic hand motion animation by the use of an anatomy based hand model and a hand gesture coding system, which we called Hand Action Coding System (HACS). This allows complex sequences of hand gestures to be animated based only on the static image of the hand gestures to be animated. This approach greatly simplifies motion data acquisition and the process of motion analysis and synthesis