Model-based segmentation and recognition of dynamic gestures in continuous video streams

  • Authors:

  • Hong Li;Michael Greenspan

  • Affiliations:

  • Electrical and Computer Engineering, 19 Union Street, Walter Light Hall, Queen's University, Kingston, Ontario, Canada K7L 3N6;Electrical and Computer Engineering, 19 Union Street, Walter Light Hall, Queen's University, Kingston, Ontario, Canada K7L 3N6 and School of Computing, 557 Goodwin Hall, Queen's University, Kingst ...

  • Venue:
  • Pattern Recognition
  • Year:
  • 2011

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Abstract

Segmentation and recognition of continuous gestures are challenging due to spatio-temporal variations and endpoint localization issues. A novel multi-scale Gesture Model is presented here as a set of 3D spatio-temporal surfaces of a time-varying contour. Three approaches, which differ mainly in endpoint localization, are proposed: the first uses a motion detection strategy and multi-scale search to find the endpoints; the second uses Dynamic Time Warping to roughly locate the endpoints before a fine search is carried out; the last approach is based on Dynamic Programming. Experimental results on two arm and single hand gestures show that all three methods achieve high recognition rates, ranging from 88% to 96% for the two arm test, with the last method performing best.