Canonical forms and orbit identification problems in machine vision

S. Takahashi; B. K. Ghosh

Canonical forms and orbit identification problems in machine vision

Mathematics and Statistics

Research output: Contribution to journal › Conference article › peer-review

Abstract

We introduce canonical forms for perspective dynamical systems under the action of a perspective group and illustrate their application to parameter identification with the aid of a single CCD camera. We show that the parameters in the canonical form can be identified uniquely using an Extended Kalman Filter (EKF).

Original language	English
Pages (from-to)	5175-5181
Number of pages	7
Journal	Proceedings of the IEEE Conference on Decision and Control
Volume	5
State	Published - 2000
Event	39th IEEE Confernce on Decision and Control - Sydney, NSW, Australia Duration: Dec 12 2000 → Dec 15 2000

Keywords

Canonical forms
Extended Kalman filter
Identification
Kronecker index
Machine vision
Parameter
Perspective dynamical systems

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title = "Canonical forms and orbit identification problems in machine vision",

abstract = "We introduce canonical forms for perspective dynamical systems under the action of a perspective group and illustrate their application to parameter identification with the aid of a single CCD camera. We show that the parameters in the canonical form can be identified uniquely using an Extended Kalman Filter (EKF).",

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T1 - Canonical forms and orbit identification problems in machine vision

AU - Takahashi, S.

AU - Ghosh, B. K.

PY - 2000

Y1 - 2000

N2 - We introduce canonical forms for perspective dynamical systems under the action of a perspective group and illustrate their application to parameter identification with the aid of a single CCD camera. We show that the parameters in the canonical form can be identified uniquely using an Extended Kalman Filter (EKF).

AB - We introduce canonical forms for perspective dynamical systems under the action of a perspective group and illustrate their application to parameter identification with the aid of a single CCD camera. We show that the parameters in the canonical form can be identified uniquely using an Extended Kalman Filter (EKF).

KW - Canonical forms

KW - Extended Kalman filter

KW - Identification

KW - Kronecker index

KW - Machine vision

KW - Parameter

KW - Perspective dynamical systems

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M3 - Conference article

AN - SCOPUS:0034440391

VL - 5

SP - 5175

EP - 5181

JO - Proceedings of the IEEE Conference on Decision and Control

JF - Proceedings of the IEEE Conference on Decision and Control

SN - 0191-2216

Y2 - 12 December 2000 through 15 December 2000

ER -

Canonical forms and orbit identification problems in machine vision

Abstract

Keywords

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