Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/2451
Title: Euclidean position estimation of static features using a moving uncalibrated camera
Authors: Nath, Nitendra
Dawson, Darren M.
Tatlıcıoğlu, Enver
Keywords: Estimation
Least squares estimation
Lyapunov methods
Nonlinear systems
Perspective vision systems
Issue Date: 2009
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Nath, N., Dawson, D. M., and Tatlıcıoğlu, E. (2009, 11-14 October). Euclidean position estimation of static features using a moving uncalibrated camera. Paper presented at the IEEE International Conference on Systems, Man and Cybernetics, SMC 2009. doi:10.1109/ICSMC.2009.5346924
Abstract: In this paper, a novel Euclidean position estimation technique using a single uncalibrated camera mounted on a moving platform is developed to asymptotically recover the three-dimensional (3D) Euclidean position of static object features. The position of the moving platform is assumed to be measurable, and a second object with known 3D Euclidean coordinates relative to the world frame is considered to be available a priori. To account for the unknown camera calibration parameters and to estimate the unknown 3D Euclidean coordinates, an adaptive least squares estimation strategy is employed based on prediction error formulations and a Lyapunov-type stability analysis. The developed estimator is proven to recover the 3D Euclidean position of the unknown object features despite the lack of knowledge of the camera calibration parameters.
Description: IEEE International Conference on Systems, Man and Cybernetics, SMC 2009; San Antonio, TX; United States; 11 October 2009 through 14 October 2009
URI: http://doi.org/10.1109/ICSMC.2009.5346924
http://hdl.handle.net/11147/2451
ISSN: 1062-922X
1062-922X
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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