Kinematic calibration of an active camera system

Young, Gin-Shu; Hong, Tsai Hong; Herman, Martin; Yang, Juan

doi:10.6028/nist.ir.4715

Cited by 3 publications

(2 citation statements)

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“…The relationship between the end-effector and the camera is then described by a homogenous transform AX = XB, where A and B are matrices representing the change in end-effector and camera position respectively, while X is the unknown transform representing the extrinsic parameters, a problem first conveyed by Shiu & Ahmad [2]. Young et al [3] used a Denavit-Hartenberg model of the manipulator to simplify the problem, while Park & Martin [4] found a solution using Lie theory and least squares. Remy et al [5] solved for the extrinsic parameters as well as simultaneously determining the structure of the calibration object, while Li [6] decomposed the transformation matrix into its rotational and translational components resulting in two independent equations which could be solved separately.…”

Section: Introductionmentioning

confidence: 99%

Adaptive camera calibration with measurable position of fixed features

Kapadia

Braganza

Dawson

et al. 2008

2008 American Control Conference

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In this paper, a novel self-calibration method is developed for a camera attached to a mechanical system with known kinematics. An innovative least squares estimator is developed to compute the unknown intrinsic and extrinsic camera calibration parameters while an adaptive parameterized error prediction formulation is presented to compensate for the unknown pixel coordinates of the static objects projection. The estimator is based on a Lyapunov stability analysis which verifies convergence of the signals provided a persistent excitation condition is satisfied. Simulation results with and without additive pixel noise are also provided to illustrate the performance and robustness of the algorithm.

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Section: Introductionmentioning

confidence: 99%

Adaptive camera calibration with measurable position of fixed features

Kapadia

Braganza

Dawson

et al. 2008

2008 American Control Conference

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“…Young et al [9] describe a method where the 3D motion between different robot positions is recovered by analysing the image contents. This motion is compared to a nominal motion of separately moved axes of the robot.…”

Section: Introductionmentioning

confidence: 99%

Easy calibration of pan/tilt camera heads and online computation of the epipolar correspondences

Spiess

1997

Image Analysis and Processing

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In this article we describe a calibration procedure of a binocular camera head with two independent pan and tilt axes. For the calibration procedure itself no separate rotations of the respective axes and no fixation is required. To get reliable calibration data just a plane surface with known 2D coordinates of distinguishable target points is needed. This publication describes facts and techniques that axe known to the robotic people but mostly unknown to the computer vision society.

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