Real-time classification of dynamic hand gestures from marker-based position data

In this paper we describe plans for a dynamic hand gesture recognition system based on motion capture cameras with unlabeled markers. The intended classifier is an extension of previous work on static hand gesture recognition in the same environment. The static gestures are to form the basis of a vocabulary that will allow precise descriptions of various expressive hand gestures when combined with inferred motion and temporal data. Hidden Markov Models and dynamic time warping are expected to be useful tools in achieving this goal.