Constructing finite state machines for fast gesture recognition

Pengyu Hong, Matthew Turk, Thomas S. Huang

Research output: Contribution to journalArticlepeer-review


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 languageEnglish (US)
Pages (from-to)691-694
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Issue number3
StatePublished - 2000

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition


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