Finding Motion Primitives in Human Body Gestures

In the last decade speech processing has been applied in commercially available products. One of the key reasons for its success is the identification and use of an underlying set of generic symbols (phonemes) constituting all speech. In this work we follow the same approach, but for the problem of human body gestures. That is, the topic of this paper is how to define a framework for automatically finding primitives for human body gestures. This is done by considering a gesture as a trajectory and then searching for points where the density of the training data is high. The trajectories are re-sampled to enable a direct comparison between the samples of each trajectory, and enable time invariant comparisons. This work demonstrates and tests the primitive’s ability to reconstruct sampled trajectories. Promising test results are shown for samples from different test persons performing gestures from a small one armed gesture set.