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.
| Original language | English |
|---|---|
| Pages (from-to) | 999-1009 |
| Number of pages | 11 |
| Journal | Pattern Recognition |
| Volume | 37 |
| Issue number | 5 |
| DOIs | |
| Publication status | Published - May 2004 |
Keywords
- Gesture recognition
- Skin history images
- Composite history images
- Moment features
- Hidden Markov models