Structure from Motion with variable focal length: Interconnected fuzzy observer

R. Benyoucef, H. Hadj-Abdelkader, L. Nehaoua, Hichem Arioui
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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 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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变焦距运动结构:互联模糊观测器
本文利用部分标定的低成本单目相机,提出了一种三维点特征深度和相机焦距估计方法。相机的内在参数是已知的,除了焦距,焦距可能在不同的视图中变化。采用动态扩展方法对摄像机视角投影模型进行扩充,然后将其分解为两个相互关联的子系统。将子系统描述为具有不可测前提变量的准线性变参数系统,并为其设计了互联模糊观测器。给出了保证观察者存在的充分必要条件。基于李雅普诺夫理论结合李普奇茨条件进行了误差收敛分析。为了保证估计误差的渐近稳定性,采用线性矩阵不等式(LMI)计算增益,特征值在LMI区域聚类,以提高估计性能。
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