Multiple views gait recognition using view transformation model based on optimized gait energy image

Worapan Kusakunniran*, Qiang Wu, Hongdong Li, Jian Zhang

*Corresponding author for this work

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

    192 Citations (Scopus)

    Abstract

    Gait is one of well recognized biometrics that has been widely used for human identification. However, the current gait recognition might have difficulties due to viewing angle being changed. This is because the viewing angle under which the gait signature database was generated may not be the same as the viewing angle when the probe data are obtained. This paper proposes a new multi-view gait recognition approach which tackles the problems mentioned above. Being different from other approaches of same category, this new method creates a so called View Transformation Model (VTM) based on spatial-domain Gait Energy Image (GEI) by adopting Singular Value Decomposition (SVD) technique. To further improve the performance of the proposed VTM, Linear Discriminant Analysis (LDA) is used to optimize the obtained GEI feature vectors. When implementing SVD there are a few practical problems such as large matrix size and over-fitting. In this paper, reduced SVD is introduced to alleviate the effects caused by these problems. Using the generated VTM, the viewing angles of gallery gait data and probe gait data can be transformed into the same direction. Thus, gait signatures can be measured without difficulties. The extensive experiments show that the proposed algorithm can significantly improve the multiple view gait recognition performance when being compared to the similar methods in literature.

    Original languageEnglish
    Title of host publication2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
    Pages1058-1064
    Number of pages7
    DOIs
    Publication statusPublished - 2009
    Event2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009 - Kyoto, Japan
    Duration: 27 Sept 20094 Oct 2009

    Publication series

    Name2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009

    Conference

    Conference2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops 2009
    Country/TerritoryJapan
    CityKyoto
    Period27/09/094/10/09

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