Monocular Vision Ranging and Camera Focal Length Calibration

Liu, Xue; Li, Meian; Fan, Liang; Sun, Aixia; Gao, Tian

doi:10.1155/2021/9979111

Cited by 4 publications

(4 citation statements)

References 19 publications

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“…3) The ranging method proposed by Xue [20]. This paper is an in-depth study based on Xue's method, aiming to clarify the effect of camera height on camera calibration and ranging results, so a comparison with Xue's method is also needed.…”

Section: Compare With Other Methodsmentioning

confidence: 99%

“…The calibration method proposed by Xue et al [20] links the geometric ranging model and the focal length calibration together, differs from the previous calibration idea of correcting the pixel coordinates with distortion. In this method, the distortion and defocusing phenomena caused by the nonlinear imaging of the camera are innovatively compensated to the focal length of each pixel point, so the focal length of the camera is not considered as a constant value in this calibration method, and the expression of the focal length of a pixel point with its physical coordinates needs to be obtained using polynomial regression.…”

Section: Literature Surveymentioning

confidence: 99%

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Height-Variable Monocular Vision Ranging Technology for Smart Agriculture

Gao,

Li,

Xue

et al. 2023

IEEE Access

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Smart agriculture utilizes a variety of advanced technologies to promote sustainable agriculture and provide solutions for intelligent, automated and unmanned agriculture. Agricultural robots and related technologies are an important part of smart agriculture, while autonomous navigation is a core function of autonomous agricultural robots, which rely on information about the distance of obstacles in a scene to support decision making. In this paper, we propose a ground point geometric ranging model, which can be used in camera height dynamic change scenarios, and the method is validated by model derivation and hypothesis testing. The model combines ranging and camera calibration, choosing to compensate for distortion and defocus phenomena caused by nonlinear imaging of the camera to the focal length, and completes the parameter calibration using a small amount of ground point real distance data. In this paper, the YOLOv8 model is used to identify and range outdoor cattle, and the experimental results show that the lowest range accuracy of this method reaches 95%, this method eliminates the dependence on camera height for focal calibration in ranging models, and in practice requires only once focal calibration for permanent use, achieving a significant reduction in the complexity of focal calibration, and the migrability of the model in scenarios where the camera height changes.

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Section: Compare With Other Methodsmentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

Height-Variable Monocular Vision Ranging Technology for Smart Agriculture

Gao,

Li,

Xue

et al. 2023

IEEE Access

Self Cite

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“…Previous studies have shown that [10], when the height of the monocular surveillance camera and the target feature points are fixed, the pixel coordinates of the ground feature points of the measured object can be converted into world coordinates, thereby calculating the Euclidean distance between the camera and the world coordinates of the target feature points. This article uses Xue Lixia's monocular vision ranging model to derive a two-dimensional positioning model for ground feature points of image targets based on monocular vision.…”

Section: Introductionmentioning

confidence: 99%

A 2D Localization Model for Image Targets Based on Monocular Vision

Lian,

Li,

et al. 2024

Advances in Transdisciplinary Engineering

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With the development of artificial intelligence and the continuous deepening of visual surveillance applications, how to quickly and accurately locate targets in images and videos has become a hot research topic in the industry. This article proposes a two-dimensional feature point localization method based on a monocular vision ranging model to address the issues of low accuracy and speed in existing monocular vision feature point localization. This method fits the world coordinates of feature points by converting pixel coordinates into world coordinates and establishing a compensation model based on errors. The experiment shows that the average relative accuracy of world coordinates after error compensation reaches 98.590%, improving the accuracy of monocular visual positioning.

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“…It is frequently employed in research areas such as visual navigation [3], traffic safety [4], visual obstacle avoidance [5], and others. The two primary visual ranging techniques are monocular vision measurement and stereo vision measurement [6]. By utilizing the parallax concept, stereo vision can measure distance, but accurate feature point matching is challenging and can result in subpar real-time performance [7].…”

Section: Introductionmentioning

confidence: 99%

Visual Ranging Based on Object Detection Bounding Box Optimization

Shi,

Li,

Che

et al. 2023

Applied Sciences

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Faster and more accurate ranging can be achieved by combining the object detection technique based on deep learning with conventional visual ranging. However, changes in scene, uneven lighting, fuzzy object boundaries and other factors may result in a non-fit phenomenon between the detection bounding box and the object. The pixel spacing between the detection bounding box and the object can cause ranging errors. To reduce pixel spacing, increase the degree of fit between the object detection bounding box and the object, and improve ranging accuracy, an object detection bounding box optimization method is proposed. Two evaluation indicators, WOV and HOV, are also proposed to evaluate the results of bounding box optimization. The experimental results show that the pixel width of the bounding box is optimized by 1.19~19.24% and the pixel height is optimized by 0~12.14%. At the same time, the ranging experiments demonstrate that the optimization of the bounding box improves the ranging accuracy. In addition, few practical monocular range measurement techniques can also determine the distance to an object whose size is unknown. Therefore, a similar triangle ranging technique based on height difference is suggested to measure the distance to items of unknown size. A ranging experiment is carried out based on the optimization of the detecting bounding box, and the experimental results reveal that the ranging relative error within 6 m is between 0.7% and 2.47%, allowing for precise distance measurement.

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Monocular Vision Ranging and Camera Focal Length Calibration

Cited by 4 publications

References 19 publications

Height-Variable Monocular Vision Ranging Technology for Smart Agriculture

Height-Variable Monocular Vision Ranging Technology for Smart Agriculture

A 2D Localization Model for Image Targets Based on Monocular Vision

Visual Ranging Based on Object Detection Bounding Box Optimization

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