Camera calibration for anamorphic lenses with three-dimensional targets

Zhang, Jinkai; Wang, Xue; Ma, Miao; Li, Fajia; Liu, Haining; Cui, Huanyong

doi:10.1364/ao.59.000324

Cited by 5 publications

(6 citation statements)

References 14 publications

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“…The imaging model of anamorphic lenses differs from the traditional pinhole imaging model of spherical lenses. The anamorphic distance and the anamorphic angle are introduced as new extra intrinsic parameters [ 16 ]. Figure 1 depicts the imaging model of anamorphic lenses, where ad denotes the anamorphic distance, and aa denotes the anamorphic angle.…”

Section: Anamorphic Imaging Modelmentioning

confidence: 99%

“…Anamorphic lenses are increasingly employed in the film industry to capture wide images for broad screens [ 13 , 14 , 15 ]. Anamorphic lenses are distinguished by two characteristics: double focal lengths and double optical centers [ 16 , 17 , 18 ]. Double focal lengths means the focal lengths differ greatly in the tangential and sagittal planes.…”

Section: Introductionmentioning

confidence: 99%

“…F. Blais performed an exploratory calibration of anamorphic lenses based on a pinhole imaging model [ 24 ]. In our previous work, a high-precision anamorphic lens calibration method was proposed with 3D and 2D calibration targets [ 16 , 25 ].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

3D Metrology Using One Camera with Rotating Anamorphic Lenses

Chen

Zhang

2022

Sensors

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In this paper, a novel 3D metrology method using one camera with rotating anamorphic lenses is presented based on the characteristics of double optical centers for anamorphic imaging. When the anamorphic lens rotates −90° around its optical axis, the 3D data of the measured object can be reconstructed from the two anamorphic images captured before and after the anamorphic rotation. The anamorphic lens imaging model and a polynomial anamorphic distortion model are firstly proposed. Then, a 3D reconstruction model using one camera with rotating anamorphic lenses is presented. Experiments were carried out to validate the proposed method and evaluate its measurement accuracy. Compared with stereo vision, the main advantage of the proposed 3D metrology approach is the simplicity of point matching, which makes it suitable for developing compact sensors for fast 3D measurements, such as car navigation applications.

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Section: Anamorphic Imaging Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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3D Metrology Using One Camera with Rotating Anamorphic Lenses

Chen

Zhang

2022

Sensors

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“…A correlation coefficient ξ (p, d) is defined to describe the correlation between the corners of the two checkerboard images. The interval range is [−1, 1] (The greater the value of the correlation coefficient, the better its correlation will be): (12), as shown at the bottom of the next page. I 1 (x, y) represents the pixel value at point(x, y) in the subgraph of the left checkerboard image.Ī 1 (p x , p y ) andĪ 1 (p x + d, p y ) represent the average of the position of the pixel to be matched and the target pixel, respectively.…”

Section: Algorithm Design and Principle Of Homonymous Corner Matchmentioning

confidence: 99%

“…The calibration accuracy of the binocular camera directly affects the accuracy of the final imaging system. The traditional calibration methods of binocular camera mostly rely on the accurate imaging mathematical model, which takes little account of various nonlinear distortion factors in the imaging process, and the calibration process is relatively complicated [12]- [14]. The calibration of binocular camera determines the internal and external parameters of the imaging system for binocular stereo vision.…”

Section: Introductionmentioning

confidence: 99%

Research on the Calibration of Binocular Camera Based on BP Neural Network Optimized by Improved Genetic Simulated Annealing Algorithm

2020

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The Back Propagation (BP) neural network has the problems of low accuracy and poor convergence in the process of binocular camera calibration. A method based on BP neural network optimized by improved genetic simulated annealing algorithm (IGSAA-BP) is proposed to solve these problems to complete the binocular camera calibration. The method of combining Gaussian scale space and Harris corner detection operator is used for corner detection. A matched algorithm of homonymous corner is proposed by combining point-to-point spatial mapping and grid motion statistics. The pixel values of the homonymous corner and three-dimensional coordinate values are taken as the input and output of BP neural network respectively. The crossover and mutation probability of genetic simulated annealing algorithm and the annealing criterion are improved, the IGSAA-BP neural network is used to calibrate the binocular camera. The average calibration accuracy of BP neural network and IGSAA-BP neural network is 0.71mm and 0.03mm, respectively. The average calibration accuracy of binocular camera is improved by 96%. The iteration speed is increased by 20 times and global optimization ability is improved. It can be seen that the IGSAA-BP neural network can improve the calibration accuracy of binocular camera and accelerate convergence speed.INDEX TERMS Camera calibration, genetic simulated annealing algorithm, Gaussian scale space, corner detection, homonymous corner match, BP neural network.

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High-precision anamorphic lens calibration with 3D and 2D calibration targets

Zhang

Chen

2022

Appl. Opt.

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This paper presents a high-precision camera calibration approach for anamorphic lenses. The distortion model for anamorphic lenses is substantially more sophisticated than the distortion model for spherical lenses for the adaption of cylindrical lenses in anamorphic lens attachments. Based on the anamorphic aberration theory and numerical experiments, a polynomial type distortion model is provided for anamorphic lenses, with which high-precision camera calibrations can be achieved using 3D calibration targets. 3D calibration targets are typically limited in size, unable to encompass the whole imaging field of anamorphic lenses. The calibration results using 3D calibration targets tend to be unstable with the increased number of distortion coefficients in the anamorphic distortion model. Thus, after the anamorphic lenses have been calibrated with 3D calibration targets, they are recalibrated with 2D calibration targets that may fill the anamorphic lenses’ field of view, resulting in more dependable and exact calibration results. Two anamorphic lenses are calibrated with high precision at the end the paper, which proves the effectiveness of the proposed method.

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Camera calibration for anamorphic lenses with three-dimensional targets

Cited by 5 publications

References 14 publications

3D Metrology Using One Camera with Rotating Anamorphic Lenses

3D Metrology Using One Camera with Rotating Anamorphic Lenses

Research on the Calibration of Binocular Camera Based on BP Neural Network Optimized by Improved Genetic Simulated Annealing Algorithm

High-precision anamorphic lens calibration with 3D and 2D calibration targets

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