An Iterative Parameter Estimation Method for Observation Models with Nonlinear Constraints

• Autorzy: Dang T.
• Języki publikacji: EN

Abstrakty

EN

This article presents a parameter estimation algorithm for observation models with nonlinear constraints. A prominent example that belongs to this category is the continuous auto-calibration of stereo cameras. Here, our knowledge of the relation between the available measurements and the desired parameters is given by a nonlinear implicit constraint equation. An estimation method derived from an Iterated Extended Kalman Filter is designed for this application. Experiments are conducted with synthetic and real data. The proposed algorithm provides very good results and is readily applicable to a wider range of applications.

Słowa kluczowe

EN

recursive estimation; Kalman filter; stereo vision; self-calibration

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2008
• Tom: Vol. 15, nr 4
• Strony: 421--432
• Opis fizyczny: Bibliogr. 17 poz., rys., tab., wykr.

Twórcy

autor

Dang T.

• University of Karlsruhe, Institut f¨ur Mess- und Regelungstechnik, Karlsruhe, Germany,

Bibliografia

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