On the dynamic time warping for computing the dissimilarity between curves

Abstract

Dynamic time warping (DTW) is a technique for aligning curves that considers two aspects of variations: horizontal and vertical, or domain and range. This alignment is an essential preliminary in many applications before classification or functional data analysis. A problem with DTW is that the algorithm may fail to find the natural alignment of two series since it is mostly influenced by salient features rather than by the overall shape of the sequences. In this paper, we first deepen the DTW algorithm, showing relationships and differences with the curve registration technique, and then we propose a modification of the algorithm that considers a smoothed version of the data.