GestureRecognitionToolkit  Version: 0.2.0
The Gesture Recognition Toolkit (GRT) is a cross-platform, open-source, c++ machine learning library for real-time gesture recognition.
DTW.h File Reference

This class implements Dynamic Time Warping. Dynamic Time Warping (DTW) is a powerful classifier that works very well for recognizing temporal gestures. Temporal gestures can be defined as a cohesive sequence of movements that occur over a variable time period. The DTW algorithm is a supervised learning algorithm that can be used to classify any type of N-dimensional, temporal signal. The DTW algorithm works by creating a template time series for each gesture that needs to be recognized, and then warping the realtime signals to each of the templates to find the best match. The DTW algorithm also computes rejection thresholds that enable the algorithm to automatically reject sensor values that are not the K gestures the algorithm has been trained to recognized (without being explicitly told during the prediction phase if a gesture is, or is not, being performed). You can find out more about the DTW algorithm in Gillian, N. (2011) Recognition of multivariate temporal musical gestures using n-dimensional dynamic time warping. More...

Go to the source code of this file.

Classes

class  IndexDist
 
class  DTWTemplate
 
class  DTW
 

Detailed Description

This class implements Dynamic Time Warping. Dynamic Time Warping (DTW) is a powerful classifier that works very well for recognizing temporal gestures. Temporal gestures can be defined as a cohesive sequence of movements that occur over a variable time period. The DTW algorithm is a supervised learning algorithm that can be used to classify any type of N-dimensional, temporal signal. The DTW algorithm works by creating a template time series for each gesture that needs to be recognized, and then warping the realtime signals to each of the templates to find the best match. The DTW algorithm also computes rejection thresholds that enable the algorithm to automatically reject sensor values that are not the K gestures the algorithm has been trained to recognized (without being explicitly told during the prediction phase if a gesture is, or is not, being performed). You can find out more about the DTW algorithm in Gillian, N. (2011) Recognition of multivariate temporal musical gestures using n-dimensional dynamic time warping.

Author
Nicholas Gillian ngill.nosp@m.ian@.nosp@m.media.nosp@m..mit.nosp@m..edu
Version
1.0

The DTW algorithm is part of the GRT classification modules.

Remarks
This implementation is based on Gillian, N. (2011) Recognition of multivariate temporal musical gestures using n-dimensional dynamic time warping.

Definition in file DTW.h.