TR2017-095
Koopman-operator Observer-based Estimation of Pedestrian Crowd Flows
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- "Koopman-operator Observer-based Estimation of Pedestrian Crowd Flows", World Congress of the International Federation of Automatic Control (IFAC), DOI: 10.1016/j.ifacol.2017.08.2428, July 2017, vol. 50, pp. 14028-14033.BibTeX TR2017-095 PDF
- @inproceedings{Benosman2017jul,
- author = {Benosman, Mouhacine and Mansour, Hassan and Huroyan, Vahan},
- title = {Koopman-operator Observer-based Estimation of Pedestrian Crowd Flows},
- booktitle = {World Congress of the International Federation of Automatic Control (IFAC)},
- year = 2017,
- volume = 50,
- number = 1,
- pages = {14028--14033},
- month = jul,
- publisher = {Elsevier},
- doi = {10.1016/j.ifacol.2017.08.2428},
- url = {https://www.merl.com/publications/TR2017-095}
- }
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- "Koopman-operator Observer-based Estimation of Pedestrian Crowd Flows", World Congress of the International Federation of Automatic Control (IFAC), DOI: 10.1016/j.ifacol.2017.08.2428, July 2017, vol. 50, pp. 14028-14033.
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MERL Contact:
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Research Areas:
Digital Video, Dynamical Systems
Abstract:
We present here some preliminary results on the problem of estimating pedestrian crowds from limited measurements. More specifically, we focus on a data-driven operator-based approach. We use the Koopman operator and its approximation with the kernel dynamic mode decomposition kDMD, to design a dynamical observer, which allows us to estimate the full crowd flow, based on a partial-view of a sensing camera. We explain the dynamical observer design, discuss its limitations, and propose some numerical simulations to validate the proposed approach.