Calibration of omnidirectional cameras in practice: A comparison of methods

Puig, Luis; Bermudez, J.C.M.; Sturm, Peter; Guerrero, J. J.

doi:10.1016/j.cviu.2011.08.003

Cited by 73 publications

(35 citation statements)

References 41 publications

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“…While there exists a large body of literature on omnidirectional camera calibration [15], [16], [17], [18], localization [19], [20] and sparse structure-from-motion / SLAM [21], [22], [23], surprisingly little research has been carried out towards dense 3D reconstruction with catadioptric cameras.…”

Section: Related Workmentioning

confidence: 99%

Omnidirectional 3D reconstruction in augmented Manhattan worlds

Schoenbein

Geiger

2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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Abstract-This paper proposes a method for high-quality omnidirectional 3D reconstruction of augmented Manhattan worlds from catadioptric stereo video sequences. In contrast to existing works we do not rely on constructing virtual perspective views, but instead propose to optimize depth jointly in a unified omnidirectional space. Furthermore, we show that plane-based prior models can be applied even though planes in 3D do not project to planes in the omnidirectional domain. Towards this goal, we propose an omnidirectional slanted-plane Markov random field model which relies on plane hypotheses extracted using a novel voting scheme for 3D planes in omnidirectional space. To quantitatively evaluate our method we introduce a dataset which we have captured using our autonomous driving platform AnnieWAY which we equipped with two horizontally aligned catadioptric cameras and a Velodyne HDL-64E laser scanner for precise ground truth depth measurements. As evidenced by our experiments, the proposed method clearly benefits from the unified view and significantly outperforms existing stereo matching techniques both quantitatively and qualitatively. Furthermore, our method is able to reduce noise and the obtained depth maps can be represented very compactly by a small number of image segments and plane parameters.

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Section: Related Workmentioning

confidence: 99%

Omnidirectional 3D reconstruction in augmented Manhattan worlds

Schoenbein

Geiger

2014

2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

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“…advantages of this calibration method is its ease of implementation and its accuracy (e.g., Puig et al, 2012, for a comparative benchmark between several calibration methods for omnidirectional cameras).…”

Section: Camera Projection Model Calibration and Image Undistortionmentioning

confidence: 99%

All-sky photogrammetry techniques to georeference a cloud field

Crispel

Roberts

2018

Atmos. Meas. Tech.

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Abstract. In this study, we present a novel method of identifying and geolocalizing cloud field elements from a portable all-sky camera stereo network based on the ground and oriented towards zenith. The methodology is mainly based on stereophotogrammetry which is a 3-D reconstruction technique based on triangulation from corresponding stereo pixels in rectified images. In cases where clouds are horizontally separated, identifying individual positions is performed with segmentation techniques based on hue filtering and contour detection algorithms. Macroscopic cloud field characteristics such as cloud layer base heights and velocity fields are also deduced. In addition, the methodology is fitted to the context of measurement campaigns which impose simplicity of implementation, auto-calibration, and portability.Camera internal geometry models are achieved a priori in the laboratory and validated to ensure a certain accuracy in the peripheral parts of the all-sky image. Then, stereophotogrammetry with dense 3-D reconstruction is applied with cameras spaced 150 m apart for two validation cases. The first validation case is carried out with cumulus clouds having a cloud base height at 1500 m a.g.l. The second validation case is carried out with two cloud layers: a cumulus fractus layer with a base height at 1000 m a.g.l. and an altocumulus stratiformis layer with a base height of 2300 m a.g.l. Velocity fields at cloud base are computed by tracking image rectangular patterns through successive shots. The height uncertainty is estimated by comparison with a Vaisala CL31 ceilometer located on the site. The uncertainty on the horizontal coordinates and on the velocity field are theoretically quantified by using the experimental uncertainties of the cloud base height and camera orientation. In the first cumulus case, segmentation of the image is performed to identify individuals clouds in the cloud field and determine the horizontal positions of the cloud centers.

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“…For the calibration of internal parameters, we referred to the single-view, omnidirectional camera calibration algorithm proposed by Mei and Rives [10] in which camera lens distortion is introduced into the projection image process and the installation error of the structure is compensated. In addition, this method provides the best results with respect to catadioptric omnidirectional systems among existing methods [18]. The first step is the single-camera calibration using the OpenSource toolbox [10] based on the unified sphere-imaging model [19].…”

Section: Single-viewpoint System Calibrationmentioning

confidence: 99%

Calibration and rectification of vertically aligned binocular omnistereo vision systems

Cai

Weng

Fan

et al. 2017

J Image Video Proc.

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Omnidirectional stereo vision systems have been widely used as primary vision sensors in intelligent robot 3D measurement tasks, which require stereo calibration and rectification. Current stereo calibration and rectification methods suffer from complex calculations or a lack of accuracy. This paper establishes a simple and effective equivalency between an omnidirectional stereo vision system and a perspective vision system by studying stereo calibration and rectification methods. First, we improved the stereo calibration method. By applying the essential matrix, the complicated calibration process of the original method is simplified. By using a manual extraction method to extract corner points, noise error is eliminated and high precision is ensured. Second, we propose a new rectification method. By using the proposed simple rectification model and calibration data, the baseline length and an accurate column-aligned image pair are easily obtained, which reduces the computation time. The proposed stereo calibration and rectification method can simply and effectively obtain two key parameters of the triangulation formula for 3D measurement tasks: baseline length and parallax. Using real data captured by equipment, we performed experiments covering all the necessary stages to obtain a high-performance omnidirectional stereo vision system. Statistical analyses of the experimental results demonstrate the effectiveness of the proposed method.

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Calibration of omnidirectional cameras in practice: A comparison of methods

Cited by 73 publications

References 41 publications

Omnidirectional 3D reconstruction in augmented Manhattan worlds

Omnidirectional 3D reconstruction in augmented Manhattan worlds

All-sky photogrammetry techniques to georeference a cloud field

Calibration and rectification of vertically aligned binocular omnistereo vision systems

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