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DTW-Based Gait Recognition from Recovered 3-D Joint Angles and Inter-ankle Distance

  • Tomasz Krzeszowski
  • Adam Switonski
  • Bogdan Kwolek
  • Henryk Josinski
  • Konrad Wojciechowski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8671)

Abstract

We present a view independent approach for 3D human gait recognition. The identification of the person is done on the basis of motion estimated by our marker-less 3D motion tracking algorithm. We show tracking performance using ground-truth data acquired by Vicon motion capture system. The identification is achieved by dynamic time warping using both joint angles and inter-joint distances. We show how to calculate approximate Euclidean distance metric between two sets of Euler angles. We compare the correctly classified ratio obtained by DTW built on unit quaternion distance metric and such an Euler angle distance metric. We then show that combining the rotation distances with inter-ankle distances and other person attributes like height leads to considerably better correctly classified ratio.

Keywords

Joint Angle Euler Angle Dynamic Time Warping Joint Rotation Gait Recognition 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Tomasz Krzeszowski
    • 3
  • Adam Switonski
    • 2
    • 4
  • Bogdan Kwolek
    • 1
  • Henryk Josinski
    • 4
  • Konrad Wojciechowski
    • 2
    • 4
  1. 1.AGH University of Science and TechnologyKrakowPoland
  2. 2.Polish-Japanese Institute of Information TechnologyBytomPoland
  3. 3.Rzeszów University of TechnologyRzeszówPoland
  4. 4.Silesian University of TechnologyGliwicePoland

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