Modelling and automated calibration of a general multi‐projective camera

Khoramshahi, Ehsan; Honkavaara, Eija

doi:10.1111/phor.12230

Cited by 8 publications

(13 citation statements)

References 34 publications

(70 reference statements)

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“…The high degree of overlap allows for marker-less calibration using Structure from Motion (SfM) techniques similar to [Barazzetti et al 2011;Slama 1980]. This is different from other existing systems that need a calibration room specifically design for this purpose, such as the Panono spherical camera [Khoramshahi and Honkavaara 2018]. Instead of fiducial markers, we find 3D features by matching 2D features across images, as described in Section 5.1.…”

Section: Camera Calibrationmentioning

confidence: 99%

An integrated 6DoF video camera and system design

et al. 2019

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Fig. 1. The commercial 16 camera system, an equirectangular depth map, and final color rendering produced from our system. Designing a fully integrated 360 • video camera supporting 6DoF head motion parallax requires overcoming many technical hurdles, including camera placement, optical design, sensor resolution, system calibration, real-time video capture, depth reconstruction, and real-time novel view synthesis. While there is a large body of work describing various system components, such as multi-view depth estimation, our paper is the first to describe a complete, reproducible system that considers the challenges arising when designing, building, and deploying a full end-to-end 6DoF video camera and playback environment. Our system includes a computational imaging software pipeline supporting online markerless calibration, high-quality reconstruction, and real-time streaming and rendering. Most of our exposition is based on a professional 16-camera configuration, which will be commercially available to film producers. However, our software pipeline is generic and can handle a variety of camera geometries and configurations. The entire calibration and reconstruction software pipeline along with example datasets is open sourced to encourage follow-up research in high-quality 6DoF video reconstruction and rendering 1 .

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Section: Camera Calibrationmentioning

confidence: 99%

An integrated 6DoF video camera and system design

et al. 2019

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“…Tommaselli et al [40,41] proposed a catadioptric omnidirectional camera calibration with the Aruco [21] 3D terrestrial calibration field. Campos et al [42], Khoramshahi and Honkavaara [43] proposed a polydioptric omnidirectional camera calibration with the coded target surface room. However, these methods [40][41][42][43] are difficult to maintain the illumination condition of room which has to be uniform to detect the coded feature points, and need a large amount of space to calibrate the target camera structures.…”

Section: Omnidirectional Camera Calibrationmentioning

confidence: 99%

“…Campos et al [42], Khoramshahi and Honkavaara [43] proposed a polydioptric omnidirectional camera calibration with the coded target surface room. However, these methods [40][41][42][43] are difficult to maintain the illumination condition of room which has to be uniform to detect the coded feature points, and need a large amount of space to calibrate the target camera structures. extrinsic calibration methods using a coded checkerboard.…”

Section: Omnidirectional Camera Calibrationmentioning

confidence: 99%

Charuco Board-Based Omnidirectional Camera Calibration Method

Lee

Seo

et al. 2018

Electronics

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In this paper, we propose a Charuco board-based omnidirectional camera calibration method to solve the problem of conventional methods requiring overly complicated calibration procedures. Specifically, the proposed method can easily and precisely provide two-dimensional and three-dimensional coordinates of patterned feature points by arranging the omnidirectional camera in the Charuco board-based cube structure. Then, using the coordinate information of the feature points, an intrinsic calibration of each camera constituting the omnidirectional camera can be performed by estimating the perspective projection matrix. Furthermore, without an additional calibration structure, an extrinsic calibration of each camera can be performed, even though only part of the calibration structure is included in the captured image. Compared to conventional methods, the proposed method exhibits increased reliability, because it does not require additional adjustments to the mirror angle or the positions of several pattern boards. Moreover, the proposed method calibrates independently, regardless of the number of cameras comprising the omnidirectional camera or the camera rig structure. In the experimental results, for the intrinsic parameters, the proposed method yielded an average reprojection error of 0.37 pixels, which was better than that of conventional methods. For the extrinsic parameters, the proposed method had a mean absolute error of 0.90° for rotation displacement and a mean absolute error of 1.32 mm for translation displacement.

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“…The first aspect of employing an optical-based MMS relates to the problem of multi-camera calibration [2][3][4][5][6][7][8][9][10][11]. Nowadays, many MMSs are equipped with multi-projective cameras (MPC) because of their sturdy design, large field of view (FOV), and promising sensor models.…”

Section: Introductionmentioning

confidence: 99%

“…A synchronous shutter mechanism is applied to take simultaneous shots (<1 msec delay). A geometric model for MPC integrated into a statistical adjustment model is proposed by many researchers, e.g., ( [9][10][11]). This model ensures desirable geometric accuracies for many tasks such as 3D mapping and surveying, 3D visualization, and texturing.…”

Section: Introductionmentioning

confidence: 99%

Accurate Calibration Scheme for a Multi-Camera Mobile Mapping System

et al. 2019

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Mobile mapping systems (MMS) are increasingly used for many photogrammetric and computer vision applications, especially encouraged by the fast and accurate geospatial data generation. The accuracy of point position in an MMS is mainly dependent on the quality of calibration, accuracy of sensor synchronization, accuracy of georeferencing and stability of geometric configuration of space intersections. In this study, we focus on multi-camera calibration (interior and relative orientation parameter estimation) and MMS calibration (mounting parameter estimation). The objective of this study was to develop a practical scheme for rigorous and accurate system calibration of a photogrammetric mapping station equipped with a multi-projective camera (MPC) and a global navigation satellite system (GNSS) and inertial measurement unit (IMU) for direct georeferencing. The proposed technique is comprised of two steps. Firstly, interior orientation parameters of each individual camera in an MPC and the relative orientation parameters of each cameras of the MPC with respect to the first camera are estimated. In the second step the offset and misalignment between MPC and GNSS/IMU are estimated. The global accuracy of the proposed method was assessed using independent check points. A correspondence map for a panorama is introduced that provides metric information. Our results highlight that the proposed calibration scheme reaches centimeter-level global accuracy for 3D point positioning. This level of global accuracy demonstrates the feasibility of the proposed technique and has the potential to fit accurate mapping purposes.

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Modelling and automated calibration of a general multi‐projective camera

Cited by 8 publications

References 34 publications

An integrated 6DoF video camera and system design

An integrated 6DoF video camera and system design

Charuco Board-Based Omnidirectional Camera Calibration Method

Accurate Calibration Scheme for a Multi-Camera Mobile Mapping System

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