Reconstruction of 3D human body pose for gait recognition

Hee Deok Yang, Seong Whan Lee

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

    15 Citations (Scopus)

    Abstract

    In this paper, we propose a novel method to reconstruct 3D human body pose for gait recognition from monocular image sequences based on top-down learning. Human body pose is represented by a linear combination of prototypes of 2D silhouette images and their corresponding 3D body models in terms of the position of a predetermined set of joints. With a 2D silhouette image, we can estimate optimal coefficients for a linear combination of prototypes of the 2D silhouette images by solving least square minimization, The 3D body model of the input silhouette image is obtained by applying the estimated coefficients to the corresponding 3D body model of prototypes, In the learning stage, the proposed method is hierarchically constructed by classifying the training data into several clusters recursively. Also, in the reconstructing stage, the proposed method hierarchically reconstructs 3D human body pose with a silhouette image. The experimental results show that our method can be efficient and effective to reconstruct 3D human body pose for gait recognition.

    Original languageEnglish
    Title of host publicationAdvances in Biometrics - International Conference, ICB 2006, Proceedings
    Pages619-625
    Number of pages7
    Publication statusPublished - 2006
    EventInternational Conference on Biometrics, ICB 2006 - Hong Kong, China
    Duration: 2006 Jan 52006 Jan 7

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume3832 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    OtherInternational Conference on Biometrics, ICB 2006
    Country/TerritoryChina
    CityHong Kong
    Period06/1/506/1/7

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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