Blind Calibration of Mobile Sensors Using Informed Nonnegative Matrix Factorization

  • Clément Dorffer
  • Matthieu Puigt
  • Gilles Delmaire
  • Gilles Roussel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9237)


In this paper, we assume several heterogeneous, geolocalized, and time-stamped sensors to observe an area over time. We also assume that most of them are uncalibrated and we propose a novel formulation of the blind calibration problem as a Nonnegative Matrix Factorization (NMF) with missing entries. Our proposed approach is generalizing our previous informed and weighted NMF method, which is shown to be accurate for the considered application and to outperform blind calibration based on matrix completion and nonnegative least squares.


Blind calibration Mobile sensor network Informed nonnegative matrix factorization Missing values 



This work was funded by the “OSCAR” project within the Région Nord – Pas de Calais “Chercheurs Citoyens” Program.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Clément Dorffer
    • 1
  • Matthieu Puigt
    • 1
  • Gilles Delmaire
    • 1
  • Gilles Roussel
    • 1
  1. 1.LISICULCO, Université Lille Nord de FranceCalaisFrance

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