Survey on zoom-lens calibration methods and techniques

Ayaz, Shirazi Muhammad; Kim, Min Young; Park, Jaechan

doi:10.1007/s00138-017-0863-1

Cited by 12 publications

(3 citation statements)

References 51 publications

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“…This work is noteworthy in that the parameters were globally optimized by a single bundle adjustment model rather than by interpolating sets of parameters estimated from discrete distances. More approaches were discussed in a review (Ayaz et al, 2017), where relevant approaches were classified based on whether they were derived from a standard calibration or a self-calibration method.…”

Section: Calibration Modelsmentioning

confidence: 99%

Improvement of an LCD-Based Calibration Site for Reliable Focus-Dependent Camera Calibration

Han

2021

KSCE J Civ Eng

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This paper proposes an improved calibration site design for reliable focus-dependent camera calibration in close-range photogrammetry. The proposed calibration site displays an adjustable checkerboard on a large liquid crystal display television (LCD TV), such that the same number of checker cells appear at the same position at any focusing distance. By adjusting the roll and pitch of the LCD TV bracket, various convergent angles were implemented in order to successfully conduct self-calibration. To obtain a greater depth of field and to facilitate reproducibility, the images were acquired using a small aperture from a camera that was firmly mounted on a distance-adjustable rail. The interior orientation parameters of the camera were estimated, and the estimation errors were assessed. The results revealed a flat error level for each focusing distance; thus, consistent reliability was achieved regardless of the focusing distance. Using the estimated parameters, a 3D measurement test was conducted, and the proposed method yielded 2% smaller root mean square error. The proposed method can be implemented easily and performs reliable and accurate focusdependent calibration.

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Section: Calibration Modelsmentioning

confidence: 99%

Improvement of an LCD-Based Calibration Site for Reliable Focus-Dependent Camera Calibration

Han

2021

KSCE J Civ Eng

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“…where κ 2 is chosen by solving F −1 2 (κ 2 ) = λ, with λ the confidence-level parameter, commonly set to 95%, and F 2 the cumulative χ 2 2 distribution.…”

Section: Matching Strategymentioning

confidence: 99%

“…The calibration of a camera network with minimal requirements of human intervention (use of calibration objects, guidance of the pose estimation process) has long represented a major field of research in computer vision and photogrammetry, with novel contributions and surveys appearing regularly [2][3][4]10,21,47,50,53]. Recently, the increased focus on safety and surveillance applications has underlined the importance of smart camera networks (the reader may refer to [36,54] for a more detailed taxonomy of the major challenges raised by smart cameras).…”

Section: Introductionmentioning

confidence: 99%

Wide baseline pose estimation from video with a density-based uncertainty model

Pellicanò

Aldea

Hégarat‐Mascle

2019

Machine Vision and Applications

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Robust wide baseline pose estimation is an essential step in the deployment of smart camera networks. In this work, we highlight some current limitations of conventional strategies for relative pose estimation in difficult urban scenes. Then, we propose a solution which relies on an adaptive search of corresponding interest points in synchronized video streams which allows us to converge robustly toward a high-quality solution. The core idea of our algorithm is to build across the image space a nonstationary mapping of the local pose estimation uncertainty, based on the spatial distribution of interest points. Subsequently, the mapping guides the selection of new observations from the video stream in order to prioritize the coverage of areas of high uncertainty. With an additional step in the initial stage, the proposed algorithm may also be used for refining an existing pose estimation based on the video data; this mode allows for performing a data-driven self-calibration task for stereo rigs for which accuracy is critical, such as onboard medical or vehicular systems. We validate our method on three different datasets which cover typical scenarios in pose estimation. The results show a fast and robust convergence of the solution, with a significant improvement, compared to single image-based alternatives, of the RMSE of ground-truth matches, and of the maximum absolute error.

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A 3D Image-Based Visual Servoing Controller for 3DOF Robot with Single Camera

Thong

Phu

2022

Computational Intelligence Methods for Green Technology and Sustainable Development

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Survey on zoom-lens calibration methods and techniques

Cited by 12 publications

References 51 publications

Improvement of an LCD-Based Calibration Site for Reliable Focus-Dependent Camera Calibration

Improvement of an LCD-Based Calibration Site for Reliable Focus-Dependent Camera Calibration

Wide baseline pose estimation from video with a density-based uncertainty model

A 3D Image-Based Visual Servoing Controller for 3DOF Robot with Single Camera

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