Abstract
Gesture recognition error rates and the qualitative nature of the errors made are heavily influenced by the choice of visual representation. A direct empirical comparison of two contrasting approaches, namely trajectory- and history-based representation, is presented. Skin colour is used as a common visual cue and recognition is based on hidden Markov models, moment features and normalised template matching. Two novel representation schemes are proposed and evaluated: (i) skin history images and (ii) composite history images which represent occluded motion. Results are reported for an application in which able-bodied and disabled subjects specify their own gesture vocabularies.
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