Hand and arm gesture recognition using the radio frequency (RF) sensing
modality proves valuable in manmachine interface and smart environment. In this
paper, we use curve matching techniques for measuring the similarity of the
maximum instantaneous Doppler frequencies corresponding to different arm
gestures. In particular, we apply both Frechet and dynamic time warping (DTW)
distances that, unlike the Euclidean (L2) and Manhattan (L1) distances, take
into account both the location and the order of the points for rendering two
curves similar or dissimilar. It is shown that improved arm gesture
classification can be achieved by using the DTW method, in lieu of L2 and L1
distances, under the nearest neighbor (NN) classifier.Comment: 6 pages, 7 figures, 2020 IEEE radar conference. arXiv admin note:
substantial text overlap with arXiv:1910.1117