Abstract
This paper proposes an approach to 2D gesture recognition that models each gesture as a Finite State Machine (FSM) in the spatial-temporal space. The model construction works in a semi-automatic way. The structure of the model is first manually decided based on the observation of the spatial topology of the data. The model is refined iteratively between two stages: data segmentation and model training. We incorporate a modified Knuth-Morris-Pratt algorithm into FSM recognition procedure to speed up the gesture recognition. The computational efficiency of the FSM recognizers allows real-time on-line performance to be achieved.
Original language | English (US) |
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Pages (from-to) | 691-694 |
Number of pages | 4 |
Journal | Proceedings - International Conference on Pattern Recognition |
Volume | 15 |
Issue number | 3 |
State | Published - 2000 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition