2021/09/02 by George Sioros, Kristian Nymoen, Sioros, George +1
Computer Science · #Anomaly Detection Techniques and Applications #Computation (stat.CO) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Information Retrieval (cs.IR) #Music and Audio Processing #Statistics Theory (math.ST) #Time Series Analysis and Forecasting
paper · pdf · doi:10.48550/arxiv.2109.00978
openalex publication_date 2021/09/02 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
We propose a novel time series averaging method based on Dynamic Time Warping (DTW). In contrast to previous methods, our algorithm preserves durational information and the distinctive durational features of the sequences due to a simple conversion of the output of DTW into a time sequence and an innovative iterative averaging process. We show that it accurately estimates the ground truth mean sequences and mean temporal location of landmarks in synthetic and real-world datasets and outperforms state-of-the-art methods.