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Persistent Homology of Attractors For Action Recognition
[article]
2016
arXiv
pre-print
In this paper, we propose a novel framework for dynamical analysis of human actions from 3D motion capture data using topological data analysis. We model human actions using the topological features of the attractor of the dynamical system. We reconstruct the phase-space of time series corresponding to actions using time-delay embedding, and compute the persistent homology of the phase-space reconstruction. In order to better represent the topological properties of the phase-space, we
arXiv:1603.05310v1
fatcat:jiqfxspzancx7m3rqd7nvu4xnu