广角镜头和多镜头的非公制校准

R. Swaminathan, S. Nayar
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引用次数: 278

摘要

用广角相机拍摄的图像往往有严重的扭曲,这将点拉向光学中心。本文提出了一种不使用任何标定对象即可恢复畸变参数的方法。扭曲导致场景中的直线在图像中显示为曲线。我们的算法旨在找到将图像曲线映射为直线的失真参数。用户沿着图像曲线选择一小组点。参数的恢复被表述为目标函数的最小化,该目标函数被设计为明确地考虑所选图像点中的噪声。给出了不同噪声水平的合成数据和真实图像的实验结果。一旦校准,从这些相机流出的图像流可以使用查找表实时地不失真。我们还介绍了这种校准方法在广角相机集群中的应用,我们称之为多镜头相机。我们将畸变校正技术应用于具有四个广角摄像头的多镜头相机,以实时创建高分辨率360度全景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Non-metric calibration of wide-angle lenses and polycameras
Images taken with wide-angle cameras tend to have severe distortions which pull points towards the optical center. This paper proposes a method for recovering the distortion parameters without the use of any calibration objects. The distortions cause straight lines in the scene to appear as curves in the image. Our algorithm seeks to find the distortion parameters that would map the image curves to straight lines. The user selects a small set of points along the image curves. Recovery of the parameters is formulated as the minimization of an objective function which is designed to explicitly account for noise in the selected image points. Experimental results are presented for synthetic data with different noise levels as well as for real images. Once calibrated, the image streams from these cameras can be undistorted in real time using look up tables. We also present an application of this calibration method for wide-angle camera clusters, which we call polycameras. We apply our distortion correction technique to a polycamera with four wide-angle cameras to create a high resolution 360 degree panorama in real-time.
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