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Carnegie Mellon Robotics Institute

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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 identi cation and model-based body part segmentation.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): Computational Symmetry

Associated Project(s): A Computational Model for Repeated Pattern Perception using Crystallographic Groups

Text Reference

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

BibTeX Reference

@inproceedings{Liu_2002_3918,
   author = "Yanxi Liu, 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",
}

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