Device Independence and Extensibility in Gesture Recognition

Device Independence and Extensibility in Gesture Recognition (2003) Eisenstein, J., et al

Eisenstein et al develop a multi-layer gesture recognition framework. From raw data, a set of postural predicates are recognized. These predicates are in turn combined into gestures by matching to gesture templates. They also implement a context history that can help predict which gesture follows a give gesture sequence. The compare to a baseline monolithic neural network

Discussion
This classifier isn't really device independent. For each different device you have to retrain the predicate recognizer. Furthermore the retraining of the predicate recognizers takes longer (more weight updates) than the single network. The extensibility comes from the fact that it uses an instance based learner. Any instance base learner should show similar performance; however, the use of predicates ultimately limits the number of gestures possible.