Human gait recognition by the fusion of motion and static spatio-temporal templates

Toby H.W. Lam, Raymond S.T. Lee, Dapeng Zhang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

94 Citations (Scopus)


In this paper, we propose a gait recognition algorithm that fuses motion and static spatio-temporal templates of sequences of silhouette images, the motion silhouette contour templates (MSCTs) and static silhouette templates (SSTs). MSCTs and SSTs capture the motion and static characteristic of gait. These templates would be computed from the silhouette sequence directly. The performance of the proposed algorithm is evaluated experimentally using the SOTON data set and the USF data set. We compared our proposed algorithm with other research works on these two data sets. Experimental results show that the proposed templates are efficient for human identification in indoor and outdoor environments. The proposed algorithm has a recognition rate of around 85% on the SOTON data set. The recognition rate is around 80% in intrinsic difference group (probes A-C) of USF data set.
Original languageEnglish
Pages (from-to)2563-2573
Number of pages11
JournalPattern Recognition
Issue number9
Publication statusPublished - 1 Sept 2007


  • Biometrics
  • Gait recognition
  • Motion silhouette contour templates
  • Static silhouette templates

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence


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