Structured light stereo catadioptric scanner based on a spherical mirror

Barone, Sandro; Neri, Paolo; Paoli, Alessandro; Razionale, Armando Viviano

doi:10.1016/j.optlaseng.2018.03.004

Cited by 11 publications

(5 citation statements)

References 33 publications

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“…In recent years, catadioptric cameras have been widely used in medical imaging [ 1 , 2 , 3 ], augmented reality [ 4 , 5 , 6 ], virtual reality [ 7 , 8 , 9 ], and three-dimensional (3D) measurement [ 10 , 11 ] or reconstruction [ 12 , 13 ] because of their large field of view, simple structure, rotational symmetry, and high performance-to-price ratio. In the aspect of 3D reconstruction or measurement, based on structured light, 3D reconstruction is an active triangulation technology, which obtains the corresponding relationship between camera image points and projection pattern points through the coding and decoding of structured light.…”

Section: Introductionmentioning

confidence: 99%

Calibration of a Catadioptric System and 3D Reconstruction Based on Surface Structured Light

Lv²,

Ai³

et al. 2022

Sensors

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In response to the problem of the small field of vision in 3D reconstruction, a 3D reconstruction system based on a catadioptric camera and projector was built by introducing a traditional camera to calibrate the catadioptric camera and projector system. Firstly, the intrinsic parameters of the camera and the traditional camera are calibrated separately. Then, the calibration of the projection system is accomplished by the traditional camera. Secondly, the coordinate system is introduced to calculate, respectively, the position of the catadioptric camera and projector in the coordinate system, and the position relationship between the coordinate systems of the catadioptric camera and the projector is obtained. Finally, the projector is used to project the structured light fringe to realize the reconstruction using a catadioptric camera. The experimental results show that the reconstruction error is 0.75 mm and the relative error is 0.0068 for a target of about 1 m. The calibration method and reconstruction method proposed in this paper can guarantee the ideal geometric reconstruction accuracy.

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Section: Introductionmentioning

confidence: 99%

Calibration of a Catadioptric System and 3D Reconstruction Based on Surface Structured Light

Lv²,

Ai³

et al. 2022

Sensors

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“…However, the most common approach is represented by two-step techniques [ 16 , 17 , 18 ], where in the first step, a direct solution of some parameters is given, and then an iterative procedure is followed in order to compute the other parameters as well as to reduce the error of the direct solution. The research on stereo camera systems calibration pushed forward the calibration of non-conventional optical setups based on mirrors (catadioptric systems), such as [ 19 , 20 , 21 , 22 ] which solve the problem of spherical mirror calibration to achieve an omnidirectional scanning.…”

Section: Introductionmentioning

confidence: 99%

Automatic Calibration of a Two-Axis Rotary Table for 3D Scanning Purposes

Bisogni

Mollaiyan

Pettinari

et al. 2020

Sensors

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Rotary tables are often used to speed up the acquisition time during the 3D scanning of complex geometries. In order to avoid manual registration of the point clouds acquired with different orientations, automatic algorithms to compensate the rotation were developed. Alternatively, a proper calibration of the rotary axis with respect to the camera system is needed. Several methods are available in the literature, but they only consider a single-axis calibration. In this paper, a method for the simultaneous calibration of both axes of the table is proposed. A checkerboard is attached to the table, and several images with different poses are acquired. An optimization algorithm is then setup to determine the orientation and the locations of the two axes. A metric to assess the calibration quality was also defined by computing the average mean reprojection error. This metric is used to investigate the optimal number and distribution of the calibration poses, demonstrating that the optimum calibration results are achieved when a wider dispersion of the calibration poses is adopted.

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“…The augmented view is useful in many applications such as three‐dimensional (3D) reconstruction [1–7], video surveillance [8], robot navigation [9], and quality control [10] among others. These applications usually require the extraction of metric information from the environment, which can only be achieved with a calibrated system.…”

Section: Introductionmentioning

confidence: 99%

“…The methods can be divided into two groups. The first group uses predefined calibration patterns such as 1D objects [11], 2D patterns made of circles or chessboards [6, 12–14], 3D patterns [15, 16], lines [17–19], polarised images [20], circles [21, 22], spheres [23, 24], and barrels [25]. The second group uses self‐calibration techniques that do not rely on any calibration pattern or prior knowledge of the scene [26–29].…”

Section: Introductionmentioning

confidence: 99%

“…Planar 2D patterns are the most common objects for camera calibration, first introduced by Zhang [30] for directional cameras, these patterns are also used for omnidirectional cameras. Calibration methods using these patterns require typically multiple acquisitions by placing the pattern in different positions such that it can be reflected by the mirrors on the image planes [6, 13, 14]. The method from [12] uses line constraints on the planar pattern.…”

Section: Introductionmentioning

confidence: 99%

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