Method for calibration accuracy improvement of projector-camera-based structured light system

Ye, Yuping; Song, Zhan

doi:10.1117/1.oe.56.7.074101

Cited by 16 publications

(6 citation statements)

References 30 publications

(37 reference statements)

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“…However, this expanded distance also allows for a wider field of view, enabling the capture of larger areas in a single scan. This benefit, though, is often counterbalanced by a noticeable decrease in the intricacy and detail of the captured data, as the spread of the light pattern over a larger area reduces its distinctiveness and the system's ability to discern fine details [49,50]. During the photography process in this study, the camera was positioned approximately 1.5 m from the slope surface, while the projector was placed approximately 1.2 m away from it.…”

Section: Calibration Of the Cameramentioning

confidence: 99%

Three-Dimensional Reconstruction and Deformation Identification of Slope Models Based on Structured Light Method

Chen,

Zhang,

Tang

et al. 2024

Sensors

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In this study, we propose a meticulous method for the three-dimensional modeling of slope models using structured light, a swift and cost-effective technique. Our approach aims to enhance the understanding of slope behavior during landslides by capturing and analyzing surface deformations. The methodology involves the initial capture of images at various stages of landslides, followed by the application of the structured light method for precise three-dimensional reconstructions at each stage. The system’s low-cost nature and operational convenience make it accessible for widespread use. Subsequently, a comparative analysis is conducted to identify regions susceptible to severe landslide disasters, providing valuable insights for risk assessment. Our findings underscore the efficacy of this system in facilitating a qualitative analysis of landslide-prone areas, offering a swift and cost-efficient solution for the three-dimensional reconstruction of slope models.

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Section: Calibration Of the Cameramentioning

confidence: 99%

Three-Dimensional Reconstruction and Deformation Identification of Slope Models Based on Structured Light Method

Chen,

Zhang,

Tang

et al. 2024

Sensors

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“…I i (u i , v i ) T represent the ideal (distortion-free) pixel image coordinates. The relationship between I i and P wi can be expressed by equation (1). Rc w represents the rotation matrix from the world frame to the camera frame.…”

Section: Calibration Of the Intrinsic Parameters Of Each Cameramentioning

confidence: 99%

“…Binocular vision technology has the advantages of fast measurement speed, high measurement accuracy, a simple structure, being noncontact, etc. It is widely used in many fields such as mechanical manufacturing [1], industrial robots [2], auto navigation [3], and 3D reconstruction [4]. Before the measurement, the parameters of the binocular vision need to be calibrated, including the intrinsic parameters of each camera and the extrinsic parameters (structure parameters) of the two cameras.…”

Section: Introductionmentioning

confidence: 99%

A simple and precise calibration method for binocular vision

Zhang

et al. 2022

Meas. Sci. Technol.

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The binocular vision is an important part of machine vision measurement. The calibration accuracy is crucial for binocular vision. As for the determination of the structure parameters of the two cameras, the existing approaches usually obtain the initial values and optimize them according to the image-space errors, object-space errors or combination of them. In the optimization process, constructing the objective function only through the image-space errors or object-space errors is not enough. Moreover, the image-space errors and object-space errors can form a variety of combinations for constructing objective function. Therefore, it is hard to choose the error criterion. The inadequate error criterion may lead to over optimized or local minima (ambiguity solution). To solve the problem above, this paper proposes a simple and precise calibration method for binocular vision based on the points distance constraints and image-space errors. The process of determining the structure parameters was divided into non-iterative and iterative parts. We calculated the structure parameters of the two cameras according to distance constraints of every two feature points non-iteratively. The results obtained in this step were set as the initial value and refined through minimizing the reprojection errors by Levenberg-Marquardt method. Because the results obtained in the non-iterative step are accurate enough, only one iteration is needed. In this way, we finish the calibration avoiding to choose the error criterions. Furthermore, our method reduces the number of iterations to improve the calibration efficiency on the premise of guaranteeing the calibration accuracy. The experimental results show the superiority of this calibration method compared with other calibration methods.

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“…A reference plane with some precisely printed markers is used for the optimization of primary calibration parameters since the traditional calibration methods rely mostly on the standard reference or the corresponding image model. Thus, before applying the projection patterns over to the measuring surface, the projector and the camera have to be calibrated with any of the techniques available in [52], [53], [54], [55].…”

Section: A Projector and Camera Calibrationmentioning

confidence: 99%

A Single-Shot, Pixel Encoded 3D Measurement Technique for Structure Light

Elahi

Zhu

et al. 2020

IEEE Access

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The Structure Light System (SLS) is a general concept and it is one of the cheapest methods for the non-contactbased 3D reconstruction. The existing single-shot SLS which is primarily based on the spatial encoding techniques are not optimal in terms of resolution and digitally encoded patterns. Those schemes are not flexible, controllable, and designed up to the level of the pixel. So, to increase the resolution and to implement a flexible controllable pattern we proposed a novel heuristic method based on the spatial neighborhood. In this paper, we propose a multi-resolution SLS which can be implemented with a set of 25 geometrical shaped distinct symbols or alphabets to use in the projection pattern as shape primitive. The size of each symbol is well defined in pixels which enabled us to have access and control up to the full resolution of the projector. The shape descriptive parameters for each symbol or alphabet are also defined and computed. To spread the alphabets in a controllable manner, a method is defined to generate a robust pseudo-random sequence of any required size with a certain number of alphanumeric bases, to be employed in the projection pattern concerning the measured resolution. This arrangement will enable us to design the projection patterns according to the required surface area and the resolution. A new technique is developed for the decoding of the captured image pattern. The decoding process depends upon the classification of symbols which is based on shape descriptive parameters. The searching in the neighborhood of a symbol is carried out through computing the location information, grid distance, and direction information to find the codewords which are used to establish the correspondence.

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Method for calibration accuracy improvement of projector-camera-based structured light system

Cited by 16 publications

References 30 publications

Three-Dimensional Reconstruction and Deformation Identification of Slope Models Based on Structured Light Method

Three-Dimensional Reconstruction and Deformation Identification of Slope Models Based on Structured Light Method

A simple and precise calibration method for binocular vision

A Single-Shot, Pixel Encoded 3D Measurement Technique for Structure Light

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