Abstract
Cyclic Dynamic Time Warping (CDTW) is a good measure of contour shapes dissimilarity, but it is computationally expensive. We introduce a lower bound for CDTW inspired in the Bunke and Bühler that leads to a significant speed up of contours classification in real tasks, as the experiments show.
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Palazón, V., Marzal, A. (2006). Speeding Up Shape Classification by Means of a Cyclic Dynamic Time Warping Lower Bound. In: Corchado, E., Yin, H., Botti, V., Fyfe, C. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2006. IDEAL 2006. Lecture Notes in Computer Science, vol 4224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11875581_53
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DOI: https://doi.org/10.1007/11875581_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45485-4
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