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Gait Sequence Analysis Using Frieze Patterns

  • Yanxi Liu
  • Robert Collins
  • Yanghai Tsin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2351)

Abstract

We analyze walking people using a gait sequence representation that bypasses the need for frame-to-frame tracking of body parts. The gait representation maps a video sequence of silhouettes into a pair of two-dimensional spatio-temporal patterns that are near-periodic along the time axis. Mathematically, such patterns are called “frieze” patterns and associated symmetry groups “frieze groups”. With the help of a walking humanoid avatar, we explore variation in gait frieze patterns with respect to viewing angle, and find that the frieze groups of the gait patterns and their canonical tiles enable us to estimate viewing direction of human walking videos. In addition, analysis of periodic patterns allows us to determine the dynamic time warping and affine scaling that aligns two gait sequences from similar viewpoints. We also show how gait alignment can be used to perform human identification and model-based body part segmentation.

Keywords

Gait Pattern Dynamic Time Warping Stride Frequency Silhouette Image Gait Sequence 
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 2002

Authors and Affiliations

  • Yanxi Liu
    • 1
  • Robert Collins
    • 1
  • Yanghai Tsin
    • 1
  1. 1.The Robotics InstituteCarnegie Mellon UniversityUSA

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