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Blind calibration of mobile sensors using informed nonnegative matrix factorization

Abstract : 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.
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Contributor : Matthieu Puigt <>
Submitted on : Thursday, March 1, 2018 - 4:14:36 PM
Last modification on : Tuesday, January 5, 2021 - 1:04:02 PM
Long-term archiving on: : Wednesday, May 30, 2018 - 2:50:56 PM


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Clément Dorffer, Matthieu Puigt, Gilles Delmaire, Gilles Roussel. Blind calibration of mobile sensors using informed nonnegative matrix factorization. 12th International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA 2015), Aug 2015, Liberec, Czech Republic. pp.497-505, ⟨10.1007/978-3-319-22482-4_58⟩. ⟨hal-01367332⟩



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