Towards view-invariant gait modeling: Computing view-normalized body part trajectories

  • Authors:

  • Frédéric Jean;Alexandra Branzan Albu;Robert Bergevin

  • Affiliations:

  • Computer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Laval University, Québec, QC, Canada G1K 7P4;Laboratory for Applied Computer Vision Algorithms, Department of Electrical and Computer Engineering, University of Victoria, Victoria, BC, Canada V8W 3P6;Computer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Laval University, Québec, QC, Canada G1K 7P4

  • Venue:
  • Pattern Recognition
  • Year:
  • 2009

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Abstract

This paper proposes an approach to compute view-normalized body part trajectories of pedestrians walking on potentially non-linear paths. The proposed approach finds applications in gait modeling, gait biometrics, and in medical gait analysis. Our approach uses the 2D trajectories of both feet and the head extracted from the tracked silhouettes. On that basis, it computes the apparent walking (sagittal) planes for each detected gait half-cycle. A homography transformation is then computed for each walking plane to make it appear as if walking was observed from a fronto-parallel view. Finally, each homography is applied to head and feet trajectories over each corresponding gait half-cycle. View normalization makes head and feet trajectories appear as if seen from a fronto-parallel viewpoint, which is assumed to be optimal for gait modeling purposes. The proposed approach is fully automatic as it requires neither manual initialization nor camera calibration. An extensive experimental evaluation of the proposed approach confirms the validity of the normalization process.