TR2017-095

Koopman-operator Observer-based Estimation of Pedestrian Crowd Flows

    •  Benosman, M., Mansour, H., Huroyan, V., "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}
      • }
  • MERL Contacts:
  • 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.