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Dynamic time warping

About: Dynamic time warping is a research topic. Over the lifetime, 6013 publications have been published within this topic receiving 133130 citations.


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Journal ArticleDOI
TL;DR: Several different machine learning methodologies are compared starting from well-established statistical feature-based methods to convolutional neural networks, and a novel application of dynamic time warping to bearing fault classification is proposed as a robust, parameter free method for race fault detection.

145 citations

Journal ArticleDOI
TL;DR: This paper introduces and compares four of the most common measures of trajectory similarity: longest common subsequence (LCSS), Fréchet distance, dynamic time warping (DTW), and edit distance, implemented in a new open source R package.
Abstract: Storing, querying, and analyzing trajectories is becoming increasingly important, as the availability and volumes of trajectory data increases. One important class of trajectory analysis is computing trajectory similarity. This paper introduces and compares four of the most common measures of trajectory similarity: longest common subsequence (LCSS), Frechet distance, dynamic time warping (DTW), and edit distance. These four measures have been implemented in a new open source R package, freely available on CRAN [19]. The paper highlights some of the differences between these four similarity measures, using real trajectory data, in addition to indicating some of the important emerging applications for measurement of trajectory similarity.

144 citations

Proceedings ArticleDOI
15 Oct 2003
TL;DR: A simple novel technique for preparing reliable reference templates to improve the recognition rate score and produces templates called crosswords reference templates (CWRTs), which can be adapted to any DTW-based speech recognition systems to improve its performance.
Abstract: One of the main problems in dynamic time-warping (DTW) based speech recognition systems are the preparation of reliable reference templates for the set of words to be recognised. This paper presents a simple novel technique for preparing reliable reference templates to improve the recognition rate score. The developed technique produces templates called crosswords reference templates (CWRTs). It extracts the reference template from a set of examples rather than one example. This technique can be adapted to any DTW-based speech recognition systems to improve its performance. The speaker-dependent recognition rate, as tested on the English digits, is improved from 85.3%, using the traditional technique to 99%, using the developed technique.

144 citations

Journal ArticleDOI
TL;DR: In this article, the authors define a new type of registration process, in which the warping functions optimize the fit of a principal components decomposition to the aligned curves, effectively the features that this process aligns.
Abstract: A registration method can be defined as a process of aligning features of a sample of curves by monotone transformations of their domain. The aligned curves exhibit only amplitude variation, and the domain transformations, called warping functions, capture the phase variation in the original curves. In this article we precisely define a new type of registration process, in which the warping functions optimize the fit of a principal components decomposition to the aligned curves. The principal components are effectively the features that this process aligns. We discuss the relationship of registration to closure of a function space under convex operations, and define consistency for registration methods. We define an explicit decomposition of functional variation into amplitude and phase partitions, and develop an algorithm for combining registration with principal components analysis, and apply it to simulated and real data.

144 citations

BookDOI
01 Jan 1997
TL;DR: This book is a collection of invited chapters by leading researchers in the world covering various aspects of motion-based recognition including lipreading, gesture recognition, facial expression recognition, gait analysis, cyclic motion detection, and activity recognition.
Abstract: Motion-based recognition deals with the recognition of an object and/or its motion, based on motion in a series of images. In this approach, a sequence containing a large number of frames is used to extract motion information. The advantage is that a longer sequence leads to recognition of higher level motions, like walking or running, which consist of a complex and coordinated series of events. Unlike much previous research in motion, this approach does not require explicit reconstruction of shape from the images prior to recognition. This book provides the state-of-the-art in this rapidly developing discipline. It consists of a collection of invited chapters by leading researchers in the world covering various aspects of motion-based recognition including lipreading, gesture recognition, facial expression recognition, gait analysis, cyclic motion detection, and activity recognition. Audience: This volume will be of interest to researchers and post- graduate students whose work involves computer vision, robotics and image processing.

143 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023236
2022471
2021341
2020416
2019420
2018377