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Gait Sequence Analysis using Frieze Patterns
Y. Liu, R. Collins, and Y. Tsin
Proceedings of the 7th European Conference on Computer Vision (ECCV'02), May, 2002.

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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 identi cation and model-based body part segmentation.

Associated center: VASC
Associated lab/group: Computational Symmetry
Associated project: A Computational Model for Repeated Pattern Perception using Crystallographic Groups

Y. Liu, R. Collins, and Y. Tsin, "Gait Sequence Analysis using Frieze Patterns," Proceedings of the 7th European Conference on Computer Vision (ECCV'02), May, 2002.

@inproceedings{Liu_2002_3918,
   author = "Yanxi Liu and Robert Collins and Yanghai Tsin",
   title = "Gait Sequence Analysis using Frieze Patterns",
   booktitle = "Proceedings of the 7th European Conference on Computer Vision (ECCV'02)",
   month = "May",
   year = "2002"
}