A journal of IEEE and CAA , publishes high-quality papers in English on original theoretical/experimental research and development in all areas of automation
Advanced Search
Volume 2 Issue 2
Apr.  2015

IEEE/CAA Journal of Automatica Sinica

  • JCR Impact Factor: 15.3, Top 1 (SCI Q1)
    CiteScore: 23.5, Top 2% (Q1)
    Google Scholar h5-index: 77， TOP 5
Turn off MathJax
Article Contents
Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2015  >  2(2): 226-232
Songmin Jia, Lijia Wang and Xiuzhi Li, "View-invariant Gait Authentication Based on Silhouette Contours Analysis and View Estimation," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 2, pp. 226-232, 2015.
Citation: Songmin Jia, Lijia Wang and Xiuzhi Li, "View-invariant Gait Authentication Based on Silhouette Contours Analysis and View Estimation," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 2, pp. 226-232, 2015.
shu

View-invariant Gait Authentication Based on Silhouette Contours Analysis and View Estimation

  • 1. College of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, China;

  • 2. College of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, China;

  • 3. Department of Information Engineering and Automation, Hebei College of Industry and Technology, Shijiazhuang 050091, China;

  • 4. College of Electronic Information & Control Engineering, Beijing University of Technology, Beijing 100124, China

Funds:

This work was supported by National Natural Science Foundation of China (61105033, 61175087).

    Abstract
  • In this paper, we propose a novel view-invariant gait authentication method based on silhouette contours analysis and view estimation. The approach extracts Lucas-Kanade based gait flow image and head and shoulder mean shape (LKGFI-HSMS) of a human by using the Lucas-Kanade's method and procrustes shape analysis (PSA). LKGFI-HSMS can preserve the dynamic and static features of a gait sequence. The view between a person and a camera is identified for selecting the target's gait feature to overcome view variations. The similarity scores of LKGFI and HSMS are calculated. The product rule combines the two similarity scores to further improve the discrimination power of extracted features. Experimental results demonstrate that the proposed approach is robust to view variations and has a high authentication rate.

     

    • FullText(HTML)
  • loading
    • References(23)
  • [1]
    Yang X C, Zhou Y, Zhang T H, Shu G. Yang J. Gait recognition based on dynamic region analysis. Signal Processing, 2008, 88(9):2350- 2356
    [2]
    Zhang E, Zhao Y W, Xiong W. Active energy image plus 2DLPP for gait recognition. Signal Processing, 2010, 90(7):2295-2302
    [3]
    Boulgouris N V, Chi Z X. Human gait recognition based on matching of body components. Pattern Recognition, 2007, 40(6):1763-1770
    [4]
    Zhang R, Vogler C, Metaxas D. Human gait recognition at sagittal plane. Image and Vision Computing, 2007, 25(3):321-330
    [5]
    Liu Y Q, Wang X. Human gait recognition for multiple views. Procedia Engineering, 2011, 15:1832-1836
    [6]
    Choudhury S D, Tjahjadi T. Silhouette-based gait recognition using Procrustes shape analysis and elliptic Fourier descriptors. Pattern Recognition, 2012, 45(9):3414-3426
    [7]
    Wang L, Tan T N, Hu W M, Ning H Z. Automatic gait recognition based on statistical shape analysis. IEEE Transactions on Image Processing, 2003, 12(9):1120-1131
    [8]
    Shutler J D, Nixon M S. Zernike velocity moments for sequence-based description of moving features. Image and Vision Computing, 2006, 24(4):343-356
    [9]
    Shutler J D, Nixon M S, Harris C J. Statistical gait description via temporal moments. In:Proceedings of the 4th IEEE Southwest Symposium on Image Analysis and Interpretation. Austin, TX:IEEE, 2004. 291-295
    [10]
    Han J, Bhanu B. Individual recognition using gait energy image. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006, 28(2):316-322
    [11]
    Roy A, Sural S, Mukherjee J. Gait recognition using pose Kinematics and pose energy image. Signal Processing, 2012, 92(3):780-792
    [12]
    Pratik C, Aditi R, Shamik S, Jayanta M. Pose depth volume extraction from RGB-D streams for frontal gait recognition. Journal of Visual Communication and Image Representation, 2014, 25(1):53-63
    [13]
    Zeng W, Wang C, Yang F F. Silhouette-based gait recognition via deterministic learning. Pattern Recognition, 2014, 47(11):3568-2584
    [14]
    Lam T H W, Cheung K H, Liu J N K. Gait flow image:a silhouettebased gait representation for human identification. Pattern Recognition, 2011, 44(4):973-987
    [15]
    Jia S M, Wang L J, Wang S, Li X Z. Personal identification combining modified gait flow image and view. Optical and Precision Engineering, 2012, 20(11):2500-2507
    [16]
    Wang L, Ning H, Tan T, Hu W. Fusion of static and dynamic body biometrics for gait recognition. IEEE Transactions on Circuits and Systems for Video Technology, 2004, 14(2):149-158
    [17]
    Barnich O, Droogenbroech M V. Frontal-view gait recognition by intraand inter-frame rectangle size distribution. Pattern Recognition Letters, 2009, 30(10):893-901
    [18]
    Bodor R, Drenner A, Fehr D, Masoud O, Papanikolopoulos N. Viewindependent human motion classification using image-based reconstruction. Image and Vision Computing, 2009, 27(8):1197-1206
    [19]
    Liu N, Lu J W, Tan Y P. Joint subspace learning for view-invariant gait recognition. IEEE Signal Processing Letters, 2011, 18(7):431-434
    [20]
    Kusakunniran W, Wu Q, Li H D, Zhang J. Multiple views gait recognition using view transformation model based on optimized gait energy image. In:Proceedings of the 12th IEEE International Conference on Computer Vision Workshops. Kyoto:IEEE, 2009. 1058-1064
    [21]
    Liu N N, Lu J W, Yang G, Tan Y P. Robust gait recognition via discriminative set matching. Journal of Visual Communication and Image Representation, 2013, 24(4):439-447
    [22]
    Wang L J, Jia S M, Li X Z, Wang S. Human gait recognition based on gait flow image considering walking direction. In:Proceedings of the 2012 IEEE International Conference on Mechatronics and Automation. Chengdu, China:IEEE, 2012. 1990-1995
    [23]
    Mowbray S D, Nixon M S. Automatic gait recognition via Fourier descriptors of deformable objects. In:Proceedings of the 4th International Conference on Audio- and Video-Based Biometric Person Authentication. Guildford:Springer-Verlag, 2003. 556-573
    • Related Articles
    • Supplements(0)

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article views (1130) PDF downloads(8) Cited by()

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return