
Implementations and Applications of Dynamic Time Warping
Source:vignettes/articles/dtw_applications.Rmd
dtw_applications.RmdSummary
This article lists open source implementations and notable applications of Dynamic Time Warping (DTW) identified in the literature, patents, and other resources. It is intended as a living document and will be updated periodically with new findings.
Open Source Implementations
This section lists several open source implementations of DTW in R and Python, for those who wish to experiment with DTW directly.
R
- dtw, by Toni Giorgino: most complete DTW suite in R, with a companion paper here. It also has a Python implementation linked below.
- dtwclust, by Alexis Sarda-Espinosa: focused on applying DTW for time series clustering. It has a very comprehensive technical vignette here.
- IncDTW, by Maximilian Leodolter: efficient implementation with a companion paper, focused on fast DTW computations for real-time applications.
Python
- dtw-python: Python implementation of dtw.
- dtaidistance: fast C implementation of DTW, with a great documentation page here.
- tslearn, by Romain Tavenard: focused on time series clustering via DTW for machine learning modeling.
- fastdtw, by Stan Salvador and Philip Chan: Python implementation of FastDTW, a fast approximation to DTW described in this paper.
Other Languages
The Wikipedia page on Dynamic Time Warping lists implementations in other languages in the section Open Source Software.
Applications
Industry
Wave ring is a MIDI controller for music creation, patented by Genki.
LAMTSS, by Toshiba, for prediction and detection of operational failures in heavy machinery.
Sift software, by HAS Motion, uses DTW to find anomalies in large biomechanics datasets.
Netflix uses Dynamic Time Warping to align soundtracks and close captions.
Academia
Classifying ball trajectories in invasion sports using dynamic time warping: A basketball case study
A Unified Framework for Quality Indexing and Classification of Seismocardiogram Signals
Using dynamic time warping for online temporal fusion in multisensor
Dynamic Time Warping as a Means of Assessing Solar Wind Time Series