• DocumentCode
    3660491
  • Title

    Gait recognition robust to dress and carrying using multi-link gravity center track

  • Author

    Tianqi Yang;Zitao Zeng;Xin Chen

  • Author_Institution
    Department of computer science, Jinan university, Guangzhou, China
  • fYear
    2015
  • Firstpage
    2813
  • Lastpage
    2816
  • Abstract
    There has been increasing interest in applying gait recognition systems to real lives. Currently, the main obstacle hindering the appearance of gait recognition system is high complexity and suffering from dress and carrying variance. In this paper, it proposes a gait recognition method based on multi-link gravity center track (ML-GCT) that has low computation cost but robust to dress and carrying. It divides human silhouette into multiple links and calculates the GCT of each link. In order to improve the recognition accuracy, it takes Fisher´s ratio as the importance score (IS) to rank body regions, then completes matching on the ranked regions. Test shows that the method is capable of achieving excellent recognition under different dress and carrying conditions.
  • Keywords
    "Gravity","Gait recognition","Clothing","Robustness","Legged locomotion","Interference","Databases"
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation, 2015 IEEE International Conference on
  • Type

    conf

  • DOI
    10.1109/ICInfA.2015.7279765
  • Filename
    7279765