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Depth Information in Human Gait Analysis: An Experimental Study on Gender Recognition

  • Ricard Borràs
  • Àgata Lapedriza
  • Laura Igual
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7325)

Abstract

This work presents DGait, a new gait database acquired with a depth camera. This database contains videos from 53 subjects walking in different directions. The intent of this database is to provide a public set to explore whether the depth can be used as an additional information source for gait classification purposes. Each video is labelled according to subject, gender and age. Furthermore, for each subject and view point, we provide initial and final frames of an entire walk cycle. On the other hand, we perform gait-based gender classification experiments with DGait database, in order to illustrate the usefulness of depth information for this purpose. In our experiments, we extract 2D and 3D gait features based on shape descriptors, and compare the performance of these features for gender identification, using a Kernel SVM. The obtained results show that depth can be an information source of great relevance for gait classification problems.

Keywords

Biometrics Gender Recognition Human Gait features 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Ricard Borràs
    • 1
  • Àgata Lapedriza
    • 1
    • 2
  • Laura Igual
    • 1
    • 3
  1. 1.Centre de Visió per ComputadorBarcelonaSpain
  2. 2.Universitat Oberta de CatalunyaSpain
  3. 3.Universitat de BarcelonaSpain

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