Scaling and time warping in time series querying

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The last few years have seen an increasing understanding that Dynamic Time Warping (DTW), a technique that allows local flexibility in aligning time series, is superior to the ubiquitous Euclidean Distance for time series classification, clustering, and indexing. More recently, it has been shown that for some problems, Uniform Scaling (US), a technique that allows global scaling of time series, may just be as important for some problems. In this work, we note that for many real world problems, it is necessary to combine both DTW and US to achieve meaningful results. This is particularly true in domains where we must account for the natural variability of human action, including biometrics, query by humming, motion-capture/animation, and handwriting recognition. We introduce the first technique which can handle both DTW and US simultaneously, and demonstrate its utility and effectiveness on a wide range of problems in industry, medicine, and entertainment.