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Structure from Motion with Variable Focal Length: Interconnected Fuzzy Observer

Abstract : In this paper, a 3D point feature depth and camera focal length estimation is proposed, using a partially calibrated low cost monocular camera. The camera intrinsic parameters are known, except for the focal length, which may vary across different views. The camera perspective projection model is augmented using dynamic extension approach, then decomposed into two interconnected subsystems. The subsystems are described as quasi-Linear Parameter Varying (qLPV) systems with unmeasured premise variables for which an Interconnected Fuzzy Observer (IFO) is designed. Necessary and sufficient conditions to ensure the observer existence are presented. The error convergence analysis is performed based on Lyapunov theory associated with Lipchitz condition. Gains that guarantee the asymptotic stability of the estimation error are computed in terms of Linear Matrix Inequalities (LMI) with eigenvalues clustering in LMI region to improve the estimation performance.
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Contributor : Frédéric Davesne Connect in order to contact the contributor
Submitted on : Friday, December 17, 2021 - 12:57:39 AM
Last modification on : Friday, April 15, 2022 - 11:08:03 AM
Long-term archiving on: : Friday, March 18, 2022 - 6:13:21 PM


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Rayane Benyoucef, Hicham Hadj-Abdelkader, Lamri Nehaoua, Hichem Arioui. Structure from Motion with Variable Focal Length: Interconnected Fuzzy Observer. 60th IEEE conference on Decision and Control (CDC 2021), Dec 2021, Austin, Texas, United States. pp.6145--6150, ⟨10.1109/CDC45484.2021.9683139⟩. ⟨hal-03484304⟩



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