Gromov-Hausdorff Stable Signatures for Shapes using Persistence

We introduce a family of signatures for finite metric spaces, possibly, endowed with real valued functions, based on the persistence diagrams of suitable filtrations built on top of these spaces. We prove the stability, of our signatures under Gromov-Hausdorff perturbations of the spaces. We also extend these results to metric spaces equipped with measures. Our signatures are well-suited for the study of unstructured point cloud data, which we illustrate through an application in shape classification.