Geometric Fusion via Joint Delay Embeddings
Abstract
We introduce geometric and topological methods to develop a new framework for fusing multi-sensor time series. This framework consists of two steps: (1) a joint delay embedding, which reconstructs a high-dimensional state space in which our sensors correspond to observation functions, and (2) a simple orthogonalization scheme, which accounts for tangencies between such observation functions, and produces a more diversified geometry on the embedding space. We conclude with some synthetic and real-world experiments demonstrating that our framework outperforms traditional metric fusion methods.
- Publication:
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arXiv e-prints
- Pub Date:
- February 2020
- DOI:
- 10.48550/arXiv.2002.11201
- arXiv:
- arXiv:2002.11201
- Bibcode:
- 2020arXiv200211201S
- Keywords:
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- Computer Science - Computer Vision and Pattern Recognition;
- Electrical Engineering and Systems Science - Signal Processing