Journal of Mathematical Imaging and Vision

, Volume 51, Issue 1, pp 209–228 | Cite as

Continuous-Discrete Extended Kalman Filter on Matrix Lie Groups Using Concentrated Gaussian Distributions

  • Guillaume Bourmaud
  • Rémi Mégret
  • Marc Arnaudon
  • Audrey Giremus


In this paper we generalize the continuous-discrete extended Kalman filter (CD-EKF) to the case where the state and the observations evolve on connected unimodular matrix Lie groups. We propose a new assumed density filter called continuous-discrete extended Kalman filter on Lie groups (CD-LG-EKF). It is built upon a geometrically meaningful modeling of the concentrated Gaussian distribution on Lie groups. Such a distribution is parametrized by a mean and a covariance matrix defined on the Lie group and in its associated Lie algebra respectively. Our formalism yields tractable equations for both non-linear continuous time propagation and discrete update of the distribution parameters under the assumption that the posterior distribution of the state is a concentrated Gaussian. As a side effect, we contribute to the derivation of the first and second order differential of the matrix Lie group logarithm using left connection. We also show that the CD-LG-EKF reduces to the usual CD-EKF if the state and the observations evolve on Euclidean spaces. Our approach leads to a systematic methodology for the design of filters, which is illustrated by the application to a camera pose filtering problem with observations on Lie group. In this application, the CD-LG-EKF significantly outperforms two constrained non-linear filters (one based on a linearization technique and the other on the unscented transform) applied on the embedding space of the Lie group.


Extended Kalman filter Matrix Lie group Filtering on manifold Stochastic processes on manifolds Camera pose filtering 



This research has received funding from the European Communitys Seventh Framework Programme (FP7/2007-2013) under Grant agreement 288199 Dem@Care


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Guillaume Bourmaud
    • 1
  • Rémi Mégret
    • 1
  • Marc Arnaudon
    • 2
  • Audrey Giremus
    • 1
  1. 1.IMS Laboratory CNRS UMR 5218University of BordeauxTalence CedexFrance
  2. 2.IMB Laboratory CNRS UMR 5251University of BordeauxTalence CedexFrance

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