Gait recognition via optimally interpolated deformable contours

  • Authors:

  • Chin Poo Lee;Alan W. C. Tan;Shing Chiang Tan

  • Affiliations:

  • Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Bukit Beruang, Melaka, Malaysia;Faculty of Engineering and Technology, Multimedia University, Jalan Ayer Keroh Lama, Bukit Beruang, 75450 Melaka, Malaysia;Faculty of Information Science and Technology, Multimedia University, Jalan Ayer Keroh Lama, 75450 Bukit Beruang, Melaka, Malaysia

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2013

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Abstract

Gait as a biometric was inspired by the ability to recognize an acquaintance by his manner of walking even when seen at a distance. In this paper, we describe a novel Fourier descriptor based gait recognition method that models the periodic deformation of human contours. A new measure of similarity using the product of Fourier coefficients is proposed as a distance measure between closed curves. In order to maximize the similarity between subsequent closed curves, the assembly of contours in gait cycle is circularly shifted by a circular permutation matrix. Subsequently, an element-wise frame interpolation is correspondingly applied to produce length invariant gait signatures. The experiments on OU-ISIR gait database and CASIA gait database reveal promising recognition accuracy. The element-wise frame interpolation method is able to preserve temporal information even when the gait cycles change, and therefore offers a better robustness to slight variation in walking speed.