Gait Recognition Using Wavelet Packet Silhouette Representation and Transductive Support Vector Machines

  • Dadashi F
  • Araabi B
  • Soltanian-Zadeh H
  • 1


    Mendeley users who have this article in their library.
  • N/A


    Citations of this article.


Gait is an idiosyncratic biometric that can be used for human
identification at a distance and as a result gained growing interest in
intelligent visual surveillance. In this paper, an efficient gait
recognition method based on describing subject outer body contour
deformations using wavelet packets is proposed. With the use of Matching
Pursuit algorithm, k bases of wavelet packet tree that have maximum
similarity to the signal are selected and corresponding coefficients are
used as features. Finally, Transductive Support vector Machine (TSVM)
classification is utilized on computed eigengait space for
semi-supervised identification. The proposed method of selecting
features which uses a complete orthogonal or near orthogonal basis from
a wavelet packet library of bases and investigating the correlational
structure of gait features for each individual using TSVM, result in
encouraging identification performance.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


  • Farzin Dadashi

  • Babak N Araabi

  • Hamid Soltanian-Zadeh

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free