PDCON:Conference/Dynamic Time Warping for Pure Data: Difference between revisions

Revision as of 17:54, 2 July 2011

Dynamic time warping for Pure Data

Authors: Pedro Lopes' and Joaquim Jorge

We present an implementation of the Dynamic Time Warping algorithm for the Pure Data programming environment. This algorithm is fairly popular in several contexts, ranging from speech processing to pattern detection, mainly because it allows to compare and recognize data sets that may vary non-linearly in time. Our contribution is easily portable to a wide number of platforms, where Pure Data is available. Throughout this document we describe relevant work that inspired our proposal and present the core concepts of our implementation.

We conclude with an evaluation of our Dynamic Time Warping implementation in two perspectives: performance and adequacy towards gesture recognition. The performance tests suggest that it is suited for realtime contexts, where algorithmic efficiency is of utmost importance. Finally we present a case study where our implementation was used successfully to accommodate gesture recognition on an existing application.

@@ Line 2: / Line 2: @@
 Authors: '''[http://pedrolopesresearch.wordpress.com Pedro Lopes]''' and ''Joaquim Jorge'''
-[[Image:http://pedrolopesresearch.files.wordpress.com/2011/07/dtw.png]]
+[[File:Dtw_help.png]]
 We present an implementation of the Dynamic Time Warping algorithm for the [[Pure Data]] programming environment. This algorithm is fairly popular in several contexts, ranging from speech processing to pattern detection, mainly because it allows to compare and recognize data sets that may vary non-linearly in time.