Development of a geometric model for an all-reflective camera system

Richter, K.; Mader, David; Seidl, K.; Maas, Hans‐Gerd

doi:10.1016/j.isprsjprs.2013.09.002

Cited by 9 publications

(4 citation statements)

References 13 publications

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“…More recent approaches are based on polynomial series such as Chebychev polynomials [11], Legendre polynomials [12], or considering Fourier series [13]. A combination of physical and mathematical models is possible as well [14,15]. Some of these approaches consist of a large number of polynomials or parameters and not all of them might be significant.…”

Section: Non-physical Models For Distortion Correctionsmentioning

confidence: 99%

“…Physical and mathematical approaches are usually well suited to correcting global distortion patterns. However, local effects may also occur, which can be corrected using the finite element method [14,16] or considering a local distortion model [17]. Luhmann et al [8] give an overview of the mathematical models and calibration techniques for a wide range of cameras.…”

Section: Non-physical Models For Distortion Correctionsmentioning

confidence: 99%

See 1 more Smart Citation

A Bi-Radial Model for Lens Distortion Correction of Low-Cost UAV Cameras

Liebold,

Mader,

Sardemann

et al. 2023

Remote Sensing

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Recently developed cameras in the low-cost sector exhibit lens distortion patterns that cannot be handled well with established models of radial lens distortion. This study presents an approach that divides the image sensor and distortion modeling into two concentric zones for the application of an extended radial lens distortion model. The mathematical model is explained in detail and it was validated on image data from a DJI Mavic Pro UAV camera. First, the special distortion pattern of the camera was examined by decomposing and analyzing the residuals. Then, a novel bi-radial model was introduced to describe the pattern. Eventually, the new model was integrated in a bundle adjustment software package. Practical tests revealed that the residuals of the bundle adjustment could be reduced by 63% with respect to the standard Brown model. On the basis of external reference measurements, an overall reduction in the residual errors of 40% was shown.

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Section: Non-physical Models For Distortion Correctionsmentioning

confidence: 99%

Section: Non-physical Models For Distortion Correctionsmentioning

confidence: 99%

A Bi-Radial Model for Lens Distortion Correction of Low-Cost UAV Cameras

Liebold,

Mader,

Sardemann

et al. 2023

Remote Sensing

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show abstract

“…Examples of omnidirectional imaging sensors are catadioptric systems, fisheye lens cameras, rotating scan cameras, and systems with multiple cameras (sets of perspective cameras with divergent optical axes) (Richter et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Calibration of Multiple Cameras and Generation of Omnidirectional Images

Pacheco,

Tommaselli

2024

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Omnidirectional images are increasingly being used in various areas, such as urban mapping, virtual reality, agriculture, and robotics. These images can be generated by different acquisition systems, including multi-camera systems, which can acquire higher-resolution images. Stitching techniques are often used and can be suitable for non-metric applications, but rigorous photogrammetric processing is recommended when having more accurate requirements. The main challenges related to this kind of product are the system calibration and the generation of the final omnidirectional images. When using multi-camera systems, the displacement of the cameras' perspective centres can affect the generation of the omnidirectional images and the resulting accuracy. A common approach to minimising the resulting parallax error is to establish a value for the projection cylinder radius as close as possible to the object's depth. This work proposes a highly accurate simultaneous calibration technique for multiple camera systems using self-calibrating bundle adjustment with constraints of stability of the relative orientation parameters. These parameters are later used to generate a projecting cylindrical surface, maintaining the original camera perspective centres and relative orientation angles. The experiments show that using constraints improved both the calibration results and the final omnidirectional images. Residual mismatches between points in overlapping areas are subpixel.

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“…Omnidirectional images can be acquired using a fisheye lens; moving cameras or optical elements; catadioptric systems (Baker and Nayar, 1999); and multiple cameras with divergent view (Sturm et al, 2011). The all-reflective system, which camera objective is based on mirrors, also enable the imagery acquisition with wide field of view (Richter et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Calibration of a catadioptric omnidirectional vision system with conic mirror

Marcato

Tommaselli

Moraes

2016

ISPRS Journal of Photogrammetry and Remote Sensing

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Omnidirectional vision systems that enable 360°imaging have been widely used in several research areas, including close-range photogrammetry, which allows the accurate 3D measurement of objects. To achieve accurate results in Photogrammetric applications, it is necessary to model and calibrate these systems. The major contribution of this paper relates to the rigorous geometric modeling and calibration of a catadioptric, omnidirectional vision system that is composed of a wide-angle lens camera and a conic mirror. The indirect orientation of the omnidirectional images can also be estimated using this rigorous mathematical model. When calibrating the system, which is composed of a wide-angle camera and a conic mirror, misalignment of the conical mirror axis with respect to the camera's optical axis is a critical problem that must be considered in mathematical models. The interior calibration technique developed in this paper encompasses the following steps: wide-angle camera calibration; conic mirror modeling; and estimation of the transformation parameters between the camera and conic mirror reference systems. The main advantage of the developed technique is that it does not require accurate physical alignment between the camera and conic mirror axis. The exterior orientation is based on the properties of the conic mirror reflection. Experiments were conducted with images collected from a calibration field, and the results verified that the catadioptric omnidirectional system allows for the generation of ground coordinates with high geometric quality, provided that rigorous photogrammetric processes are applied.

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Development of a geometric model for an all-reflective camera system

Cited by 9 publications

References 13 publications

A Bi-Radial Model for Lens Distortion Correction of Low-Cost UAV Cameras

A Bi-Radial Model for Lens Distortion Correction of Low-Cost UAV Cameras

Simultaneous Calibration of Multiple Cameras and Generation of Omnidirectional Images

Calibration of a catadioptric omnidirectional vision system with conic mirror

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