2016
Unsupervised time-series clustering of distorted and asynchronous temporal patterns
ICASSP 2016accepted
Most time-series clustering methods, such as k-means or k-medoids, are initialized by prior knowledge about the number of classes or by a learning step. We propose an unsupervised clustering technique based on spatiotemporal mean-shift and optimal time series warping using dynamic time warping (DTW)…