Signatures in Shape Analysis: an Efficient Approach to Motion Identification

Celledoni, Elena, Lystad, Pål Erik, Tapia, Nikolas

arXiv.org Machine Learning 

Signatures provide a succinct description of certain features of paths in a reparametrization invariant way. We propose a method for classifying shapes based on signatures, and compare it to current approaches based on the SRV transform and dynamic programming.

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