Minimal Vision System for Linear Camera Self-Calibration and 3D Reconstruction Using Translation Platform
Minimal Vision System for Linear Camera Self-Calibration and 3D Reconstruction Using Translation Platform
复制标题
使用平移平台进行线性相机自校准和 3D 重建的最小视觉系统
DOI：
10.1007/s11042-019-7666-5
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发表时间：
2019-05
影响因子：
3.6
通讯作者：
赵斌
中科院分区：
文献类型：
--
作者：
胡钊政;赵斌
相机校准和3D重建是计算机视觉中的两个关键步骤。借助机器人和自主漫游器系统的播放，可以广泛应用缩放摄像头，其中。在线校准和3D重建变得越来越重要。本文提出了一个最小视觉系统，该系统由翻译平台和一个未估计的Camera组成。使用该系统最小的系统，我们可以通过利用翻译动作从三个未校准的图像中进行线性校准相机3D结构。通过翻译相机以允许场景深度恢复而生成的两个图像。深度。然后通过误差分析模型进行分析，并用于确定无限的图像和两个翻译图像中的任何一个。然后，从计算的无限同构图线性地校准了固有的参数。然后，摄像机估计和3D重建很容易从固有的结果确定。我们还提出了一种两步优化的方法，通过最大程度地减少整体反向预测错误来完善量化和3D重建结果。在微小规模的束调节框架内交流了三个图像。所提出的方法已通过模拟和真实图像数据验证。结果证明了结果。提出的最小线性系统可以解决在线摄像机的自我校准问题以及3D结构的重建。该论文提出了一个最小线性的框架。系统通过使用未校准的摄像机和低成本的翻译平台来解决摄像机的线性自我校准，运动估算，3D重建以及以实用，易于和准确的方式进行的线性自我校准的问题。
Camera calibration and 3D reconstruction are two crucial steps in computer vision. With the.progress of robot and autonomous rover systems, zooming cameras are widely applied, where.online calibration and 3D reconstruction are becoming more and more important. This paper.proposed a minimal vision system that consists of a translation platform and an un-calibrated.camera mounted on.With this minimal system, we can linearly calibrate the camera online and.reconstruct 3D structures from three un-calibrated images by utilizing translation motions. The.two images generated by translating the camera to allow the recovery of scene depths. Depths.are then analyzed by error analysis models and are utilized to determine the infinite.homography between the third image and any of the two translated images. The intrinsic.parameters are then calibrated linearly from the computed infinite homography. Camera.motion estimation and 3D reconstruction are then readily determined from the intrinsic.calibration results. We also proposed a two-step optimization method to refine both the.calibration and 3D reconstruction results by minimizing the overall back-projection errors.across the three images within a tiny-scale bundle adjustment framework. The proposed.method has been validated with both simulation and real image data. The results demonstrate.that the proposed minimal linear system can solve the online camera self-calibration problem.and the reconstruction of 3D structure. The paper suggests a framework of minimal linear.system by using an un-calibrated camera and a low-cost translation platform to address the.problems of linear self-calibration of camera, motion estimation, 3D reconstruction, and.optimization, in a practical, easy, and accurate way.
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DOI：
10.1109/imtc.2011.5944093
发表时间：
2011-05
期刊：
2011 IEEE International Instrumentation and Measurement Technology Conference
影响因子：
--
作者：
Qiang Wang;Yan Liu;Yi Shen
通讯作者：
Qiang Wang;Yan Liu;Yi Shen
影响因子：
3.6
作者：
K. Kottari;K. Delibasis;V. Plagianakos
通讯作者：
K. Kottari;K. Delibasis;V. Plagianakos
DOI：
10.1109/70.481755
发表时间：
1996-02-01
期刊：
IEEE TRANSACTIONS ON ROBOTICS AND AUTOMATION
影响因子：
--
作者：
DeMa, S
通讯作者：
DeMa, S
DOI：
10.1145/1486525.1486526
发表时间：
2009-03
期刊：
ACM Trans. Math. Softw.
影响因子：
--
作者：
Jan Mayer
通讯作者：
Jan Mayer
影响因子：
5.6
作者：
G. Panahandeh;M. Jansson;P. Händel
通讯作者：
G. Panahandeh;M. Jansson;P. Händel