Biometric Gait Recognition with Carrying and Clothing Variants

  • Shamsher Singh
  • K. K. Biswas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5909)

Abstract

Compact spatio temporal representation of human gait in form of gait enery image (GEI) has attracted lot of attention in recent years for biometric gait recognition. Researchers have reported very high recognition rates for normal walk sequences. However, the rates come down when the subjects are wearing a jacket or coat, or are carrying a bag. This paper shows that the performance for the variant situations can be improved upon considerably by constructing the GEI with sway alignment instead of upper body alignment, and selecting just the required number of rows from the bottom of the silhouette as inputs for an unsupervised feature selection approach. The improvement in recognition rates are established by comparing performances with existing results on a large gait database.

Keywords

Feature Selection Recognition Rate View Angle Normal Walk High Recognition Rate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Shamsher Singh
    • 1
  • K. K. Biswas
    • 1
  1. 1.Dept. of CSEIIT DelhiIndia

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