Nothing Special   »   [go: up one dir, main page]

skip to main content
10.1109/ICPR.2010.537guideproceedingsArticle/Chapter ViewAbstractPublication PagesConference Proceedingsacm-pubtype
Article

Gait Recognition Using Period-Based Phase Synchronization for Low Frame-Rate Videos

Published: 23 August 2010 Publication History

Abstract

This paper proposes a method for period-based gait trajectory matching in the eigenspace using phase synchronization for low frame-rate videos. First, a gait period is detected by maximizing the normalized autocorrelation of the gait silhouette sequence for the temporal axis. Next, a gait silhouette sequence is expressed as a trajectory in the eigenspace and the gait phase is synchronized by time stretching and time shifting of the trajectory based on the detected period. In addition, multiple period-based matching results are integrated via statistical procedures for more robust matching in the presence of fluctuations among gait sequences. Results of experiments conducted with 185 subjects to evaluate the performance of the gait verification with various spatial and temporal resolutions, demonstrate the effectiveness of the proposed method.

Cited By

View all
  • (2022)Gait Recognition Based on Deep Learning: A SurveyACM Computing Surveys10.1145/349023555:2(1-34)Online publication date: 18-Jan-2022
  • (2019)Statistical methods for analysis of Parkinson's disease gait pattern and classificationMultimedia Tools and Applications10.1007/s11042-019-7310-478:14(19697-19734)Online publication date: 1-Jul-2019
  • (2018)A Survey on Gait RecognitionACM Computing Surveys10.1145/323063351:5(1-35)Online publication date: 29-Aug-2018
  • Show More Cited By
  1. Gait Recognition Using Period-Based Phase Synchronization for Low Frame-Rate Videos

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image Guide Proceedings
    ICPR '10: Proceedings of the 2010 20th International Conference on Pattern Recognition
    August 2010
    4662 pages
    ISBN:9780769541099

    Publisher

    IEEE Computer Society

    United States

    Publication History

    Published: 23 August 2010

    Author Tags

    1. PCA
    2. gait period
    3. gait recognition
    4. low frame rate
    5. phase synchronization

    Qualifiers

    • Article

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • Downloads (Last 12 months)0
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 16 Feb 2025

    Other Metrics

    Citations

    Cited By

    View all
    • (2022)Gait Recognition Based on Deep Learning: A SurveyACM Computing Surveys10.1145/349023555:2(1-34)Online publication date: 18-Jan-2022
    • (2019)Statistical methods for analysis of Parkinson's disease gait pattern and classificationMultimedia Tools and Applications10.1007/s11042-019-7310-478:14(19697-19734)Online publication date: 1-Jul-2019
    • (2018)A Survey on Gait RecognitionACM Computing Surveys10.1145/323063351:5(1-35)Online publication date: 29-Aug-2018
    • (2017)A study on human gait dynamicsMultimedia Tools and Applications10.1007/s11042-016-4033-776:20(21365-21400)Online publication date: 1-Oct-2017
    • (2014)Person tracking and segmentation for human gait biometric systemInternational Journal of Biometrics10.1504/IJBM.2014.0643996:3(205-230)Online publication date: 1-Aug-2014
    • (2012)Unsupervised clustering of people from 'skeleton' dataProceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction10.1145/2157689.2157767(225-226)Online publication date: 5-Mar-2012
    • (2012)Cross-view and multi-view gait recognitions based on view transformation model using multi-layer perceptronPattern Recognition Letters10.1016/j.patrec.2011.04.01433:7(882-889)Online publication date: 1-May-2012
    • (2012)LettersNeurocomputing10.1016/j.neucom.2011.10.00979(173-178)Online publication date: 1-Mar-2012
    • (2010)Phase registration of a single quasi-periodic signal using self dynamic time warpingProceedings of the 10th Asian conference on Computer vision - Volume Part III10.5555/1966049.1966102(667-678)Online publication date: 8-Nov-2010

    View Options

    View options

    Figures

    Tables

    Media

    Share

    Share

    Share this Publication link

    Share on social media