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An Incremental Dynamic Time Warping for person re-identification

  • Naresuan University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

This paper presents principles and techniques of a human gesture recognition algorithm for person identification which identifies personal gait patterns recorded with a 3D depth sensing camera, in this case the Microsoft Kinect® version 2. The recorded images are analyzed against a dataset of gait gestures derived from a sample of 37 people. We compared two algorithms for analyzing movement trajectories; Sparse code and Incremental Dynamic Time Warping (IDTW). Experimental results show that the methods have an encouraging performance. When comparing the accuracy of algorithms, IDTW gave better recognition results than the Sparse code method.

Original languageEnglish
Title of host publicationProceedings of the 2017 14th International Joint Conference on Computer Science and Software Engineering, JCSSE 2017
EditorsSiripinyo Chantamunee, Suthanya Doung-in, Putthiporn Thanathamathee
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509048342
DOIs
Publication statusPublished - 5 Sept 2017
Externally publishedYes
Event14th International Joint Conference on Computer Science and Software Engineering, JCSSE 2017 - Nakhon Si Thammarat, Thailand
Duration: 12 Jul 201714 Jul 2017

Publication series

NameProceedings of the 2017 14th International Joint Conference on Computer Science and Software Engineering, JCSSE 2017

Conference

Conference14th International Joint Conference on Computer Science and Software Engineering, JCSSE 2017
Country/TerritoryThailand
CityNakhon Si Thammarat
Period12/07/1714/07/17

Keywords

  • Gesture recognition
  • IDTW
  • Personal identification
  • Sparse code
  • recognition techniques

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