使用准直器系统的灵活相机校准

IF 9.3 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Shunkun Liang, Banglei Guan, Zhenbao Yu, Dongcai Tan, Pengju Sun, Zibin Liu, Qifeng Yu, Yang Shang
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引用次数: 0

摘要

相机校准是摄影测量和3D视觉应用的关键步骤。本文介绍了一种利用设计的准直系统对摄像机进行标定的新方法。我们的准直系统为相机提供了一个可靠、可控的标定环境。利用准直系统独特的光学几何特性,引入角度不变性约束,进一步证明了标定目标与相机之间的相对运动符合球面运动模型。该约束将目标和相机之间的原始6DOF相对运动减少为3DOF纯旋转运动。利用球面运动约束,提出了一种多图像封闭线性求解器和两图像最小求解器的相机标定方法。在此基础上,提出了一种基于角度不变性约束的单准直器图像标定算法。该算法消除了对摄像机运动的要求,为灵活快速的标定提供了一种新颖的解决方案。我们的方法在合成实验和实际实验中进行了性能评估,验证了使用准直器系统进行校准的可行性,并表明我们的方法优于现有的基线方法。演示代码可从https://github.com/LiangSK98/CollimatorCalibration获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Flexible Camera Calibration using a Collimator System

Camera calibration is a crucial step in photogrammetry and 3D vision applications. This paper introduces a novel camera calibration method using a designed collimator system. Our collimator system provides a reliable and controllable calibration environment for the camera. Exploiting the unique optical geometry property of our collimator system, we introduce an angle invariance constraint and further prove that the relative motion between the calibration target and camera conforms to a spherical motion model. This constraint reduces the original 6DOF relative motion between target and camera to a 3DOF pure rotation motion. Using spherical motion constraint, a closed-form linear solver for multiple images and a minimal solver for two images are proposed for camera calibration. Furthermore, we propose a single collimator image calibration algorithm based on the angle invariance constraint. This algorithm eliminates the requirement for camera motion, providing a novel solution for flexible and fast calibration. The performance of our method is evaluated in both synthetic and real-world experiments, which verify the feasibility of calibration using the collimator system and demonstrate that our method is superior to existing baseline methods. Demo code is available at https://github.com/LiangSK98/CollimatorCalibration.

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来源期刊
International Journal of Computer Vision
International Journal of Computer Vision 工程技术-计算机:人工智能
CiteScore
29.80
自引率
2.10%
发文量
163
审稿时长
6 months
期刊介绍: The International Journal of Computer Vision (IJCV) serves as a platform for sharing new research findings in the rapidly growing field of computer vision. It publishes 12 issues annually and presents high-quality, original contributions to the science and engineering of computer vision. The journal encompasses various types of articles to cater to different research outputs. Regular articles, which span up to 25 journal pages, focus on significant technical advancements that are of broad interest to the field. These articles showcase substantial progress in computer vision. Short articles, limited to 10 pages, offer a swift publication path for novel research outcomes. They provide a quicker means for sharing new findings with the computer vision community. Survey articles, comprising up to 30 pages, offer critical evaluations of the current state of the art in computer vision or offer tutorial presentations of relevant topics. These articles provide comprehensive and insightful overviews of specific subject areas. In addition to technical articles, the journal also includes book reviews, position papers, and editorials by prominent scientific figures. These contributions serve to complement the technical content and provide valuable perspectives. The journal encourages authors to include supplementary material online, such as images, video sequences, data sets, and software. This additional material enhances the understanding and reproducibility of the published research. Overall, the International Journal of Computer Vision is a comprehensive publication that caters to researchers in this rapidly growing field. It covers a range of article types, offers additional online resources, and facilitates the dissemination of impactful research.
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