Young and elderly, normal and pathological gait analysis using frontal view gait video data based on the statistical registration of spatiotemporal relationship

Kosuke Okusa, Toshinari Kamakura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We study the problem of analyzing and classifying frontal view gait video data. In this study, we focus on the shape scale changing in the frontal view human gait, we estimate scale parameters using the statistical registration and modeling on a video data. To demonstrate the effectiveness of our method, we apply our model to young and elderly, normal and pathological gait analysis. As a result, our model shows good performance for the scale estimation and gait analysis.

Original languageEnglish
Title of host publicationCross-Cultural Design - 8th International Conference, CCD 2016 and Held as Part of HCI International 2016, Proceedings
EditorsPei-Luen Patrick Rau
PublisherSpringer Verlag
Pages668-678
Number of pages11
ISBN (Print)9783319400921
DOIs
Publication statusPublished - 2016
Event8th International Conference on Cross-Cultural Design, CCD 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016 - Toronto, Canada
Duration: Jul 17 2016Jul 22 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9741
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Cross-Cultural Design, CCD 2016 and Held as Part of 18th International Conference on Human-Computer Interaction, HCI International 2016
CountryCanada
CityToronto
Period7/17/167/22/16

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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