A subunit-based Dynamic Time Warping (DTW) approach is proposed for hand movement recognition. Two major contributions distinguish the proposed approach from conventional DTW. (1) A set of hand movement subunits is constructed using a data-driven method. The common sub-movements (subunits) are shared across hand gestures to obtain a smaller training data size and search space to improve recognition performance. (2) A similarity measure robust to variability is offered using subunit-to-subunit matching to absorb the difference between two similar sub-sequences belonging to the same subunit, and only keeping the distances between sub-sequences that relate to different subunits. Our experimental results demonstrate the efficiency and accuracy of the proposed approach. © 2013 Springer-Verlag.
CITATION STYLE
Wang, Y., Shimada, A., Yamashita, T., & Taniguchi, R. I. (2013). A subunit-based dynamic time warping approach for hand movement recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8156 LNCS, pp. 672–681). https://doi.org/10.1007/978-3-642-41181-6_68
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