A simple and precise calibration method for binocular vision

Zhang, Zimiao; Xu, Kai; Wu, Yanan; Zhang, Shihai; Yang, Qi

doi:10.1088/1361-6501/ac4ce5

Cited by 15 publications

(7 citation statements)

References 27 publications

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“…In the stereoscopic case, used for acquisition and measurement in three dimensions, the methods are based on the calibration of the camera with two checkerboard target objects of known dimensions [6]- [8]. On the other hand, the single-camera approach, which is more similar to the problem at hand, finds several solutions in the literature.…”

Section: A) Literature Reviewmentioning

confidence: 99%

Vision-Based System for Measuring the Diameter of Wood Logs

Carratù

Gallo

Liguori

et al. 2023

IEEE Open J. Instrum. Meas.

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Detecting and measuring objects with vision-based systems in uncontrolled environments is a difficult task that today, thanks to the development of increasingly advanced artificial intelligence-based techniques, can be solved with greater ease. In this context, the paper proposes a novel approach for the vision-based measurement of objects in uncontrolled environments using a specific type of Convolutional Neural Network (CNN) named YOLO (You Only Look Once) and a Direct Linear Transformation (DLT) process. The case study concerned designing a novel vision-based system for measuring the diameter of wood logs cut and loaded onto trucks. This problem has been occurring in the Swedish forestry industry. In fact, this operation is not carried out with computer vision algorithms because of the high variability of environmental conditions caused by the changing position of the sun, weather conditions, and the variability of truck positioning. To solve this problem, the YOLO network is proposed to locate logs while attempting to maintain a high Intersection over Union (IoU) value for the correct estimation of log size. Furthermore, in order to obtain accurate measurements, the DLT is used to convert into world coordinates the dimensions of the logs themselves. The proposed CNN-based solution is described after briefly introducing today's methodologies adopted for wood bundle analysis. Particular attention is paid to both the training and the calibration steps. Results report that for 80% of cases, the error reported has been smaller than 4 cm, representing only 8% of the measurement, considering a mean log diameter for the application of 50 cm.

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Section: A) Literature Reviewmentioning

confidence: 99%

Vision-Based System for Measuring the Diameter of Wood Logs

Carratù

Gallo

Liguori

et al. 2023

IEEE Open J. Instrum. Meas.

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“…Shirai et al fed the visual information to the manipulator, controlled the movement of the manipulator, so that manipulator could complete the automatic a ssembly of the workpiece [3]. Zhang Zimiao proposed a simple and precise calibration method for binocular vision based on the points distance constraints and image-space errors [4]. Wang Fang designed a hexagon-shaped screw recognition and positioning system based on binocular vision in transformer substation [5].…”

Section: Introducingmentioning

confidence: 99%

Plugging System of Rf Connector Based on the Fusion of Monocular and Binocular Vision

Lü²,

Yang³

et al. 2023

J. Phys.: Conf. Ser.

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Aiming at the problems of poor consistency and low efficiency in the manual plugging test of 5G RF(Radio Frequency) device, an intelligent plugging system based on robotic manipulation and machine vision is proposed. The mathematical model of the RF device is firstly established. The pixel size calibration and hand-in-eye calibration algorithms are then designed. A positioning algorithm is proposed, consisted of monocular vision and binocular vision. The monocular vision is employed to calculate the position information of the 5G RF device, and consequently, the binocular vision facilitates more accurate positioning, which reduces the positioning error between the actual model and the theoretical model and improves the positioning accuracy. In the binocular ranging, this algorithm improves the traditional Census transform by adopting a double cross window and utilizing the median value of the pixels in the window as the reference value, effectively reducing the impact of noise and meanwhile preserving detailed information. The experimental results show that the average absolute error of the coordinate axis X direction is 0.33mm, the average absolute error of the coordinate axis Y direction is 0.46mm, the average absolute error of the coordinate axis Z direction is 0.27mm, and the plugging success rate is 100%.

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“…Binocular vision method uses binocular cameras with precise 3D coordinates and 3D orientations to shoot two images of the same scene simultaneously, and then geodetic coordinates of homologous image points can be calculated out according to vertical parallax of the two images. Binocular vision method has high accuracy and efficiency, and mainly focus on precise calibration of the fixed binocular cameras at present 7,8,9,10,11,12,13 , which cannot meet the dynamic requirement of UAV's patrolling video sequence images positioning.…”

Section: Introductionmentioning

confidence: 99%

A Visual Positioning Model for UAV’s Patrolling Video Sequence Images Based on DOM Rectification

Liu

Wang

2023

Preprint

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To solve the problem that existing methods cannot calculate positioning information of UAV’s (unmanned aerial vehicle) patrolling video sequence images accurately and robustly in real time, a visual positioning model is proposed, including a robust block-matching algorithm and a precise polynomial-rectifying algorithm. First, the robust block-matching algorithm is used to obtain the best matching area for UAV’s video sequence image on DOM(Digital Orthophoto Map), a preacquired digital orthophoto map covering the whole UAV’s patrolling region. Second, the precise polynomial-rectifying algorithm is used to calculate accurate rectification parameters of mapping UAV’s video sequence image to the best matching area obtained above, and then real time positioning of UAV’s patrolling video sequence images can be realized. Finally, the above two algorithms are analyzed and verified by three practical experiments, and results indicate that even if spatial resolution, surface specific features, illumination condition and topographic relief are significantly different between DOM and UAV’s patrolling video sequence images, proposed algorithms can still steadily realize positioning of UAV’s patrolling video sequence images with about 2.5m level accuracy in 1 second.

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A simple and precise calibration method for binocular vision

Cited by 15 publications

References 27 publications

Vision-Based System for Measuring the Diameter of Wood Logs

Vision-Based System for Measuring the Diameter of Wood Logs

Plugging System of Rf Connector Based on the Fusion of Monocular and Binocular Vision

A Visual Positioning Model for UAV’s Patrolling Video Sequence Images Based on DOM Rectification

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