Multiscale Detection of Gesture Patterns in Continuous Motion Trajectories

We describe a numerical method for scale invariant detection of gesture patterns in continuous 2D motions. The algorithm is fast due to our rejection-based reasoning achieved using a new set of curvature-based functions which we call Integral Absolute Curvatures. Detection rates above 96% are reported on a large data set consisting of 72,000 samples with demonstrated low execution time. The technique can be used to automatically detect gesture patterns in unconstrained motions in order to enable click-free interactions.

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