Calibration requirements and procedures for a monitor-based augmented reality system

Tüceryan, Mihran; Greer, Douglas S.; Whitaker, Ross T.; Breen, David E.; Crampton, Chris; Rose, E.; Ahlers, Klaus H.

doi:10.1109/2945.466720

Cited by 120 publications

(99 citation statements)

References 28 publications

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“…Typical approaches rely on 3D position tracking devices [31] and precise calibration [27] to ensure that the entire sequence of transformations between the internal reference frames of the virtual and physical objects, the camera tracking device, and the user's display is known exactly (Figure 1). In practice, camera calibration and position tracking are prone to errors which accumulate in the augmented display.…”

Section: Rendering Virtual Objectsmentioning

confidence: 99%

Affine object representations for calibration-free augmented reality

Kutulakos

Vallino

1996

Proceedings of the IEEE 1996 Virtual Reality Annual International Symposium

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Section: Rendering Virtual Objectsmentioning

confidence: 99%

Affine object representations for calibration-free augmented reality

Kutulakos

Vallino

1996

Proceedings of the IEEE 1996 Virtual Reality Annual International Symposium

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“…This bootstraps the second step consisting of a constraint search for additional image features (corners); thus improving the calibration. We are using the camera calibration algorithm described in [26] and implemented in [27].…”

Section: Automated Camera Calibrationmentioning

confidence: 99%

Automated camera calibration and 3D egomotion estimation for augmented reality applications

Koller

Klinker²,

Rose³

et al. 1997

Computer Analysis of Images and Patterns

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Abstract. This paper addresses the problem of accurately tracking the 3D motion of a monocular camera in a known 3D environment and dynamically estimating the 3D camera location. For that purpose we propose a fully automated landmarkbased camera calibration method and initialize a motion estimator, which employes extended Kalman filter techniques to track landmarks and to estimate the camera location at any given time. The implementation of our approach has been proven to be efficient and robust and our system successfully tracks in real-time at approximately 10 Hz. We show tracking results of various augmented reality scenarios.

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“…However, this configuration is highly specialized. Tuceyran proposed a calibration method for getting the unknown rigid transforms in the GRASP system [11]. While the method was presented as being applicable to any AR system, it uses a video see-through setup and a tracked pointer as part of the calibration procedure, however this is not the configuration of every AR systems.…”

Section: Tracker Alignment Errorsmentioning

confidence: 99%