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What Do the Sun and the Sky Tell Us About the Camera?

机译:关于相机,太阳和天空告诉我们什么?

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As the main observed illuminant outdoors, the sky is a rich source of information about the scene. However, it is yet to be fully explored in computer vision because its appearance in an image depends on the sun position, weather conditions, photometric and geometric parameters of the camera, and the location of capture. In this paper, we analyze two sources of information available within the visible portion of the sky region: the sun position, and the sky appearance. By fitting a model of the predicted sun position to an image sequence, we show how to extract camera parameters such as the focal length, and the zenith and azimuth angles. Similarly, we show how we can extract the same parameters by fitting a physically-based sky model to the sky appearance. In short, the sun and the sky serve as geometric calibration targets, which can be used to annotate a large database of image sequences. We test our methods on a high-quality image sequence with known camera parameters, and obtain errors of less that 1% for the focal length, 1° for azimuth angle and 3° for zenith angle. We also use our methods to calibrate 22 real, low-quality webcam sequences scattered throughout the continental US, and show deviations below 4% for focal length, and 3° for the zenith and azimuth angles. Finally, we demonstrate that by combining the information available within the sun position and the sky appearance, we can also estimate the camera geolocation, as well as its geometric parameters. Our method achieves a mean localization error of 110 km on real, low-quality Internet webcams. The estimated viewing and illumination geometry of the scene can be useful for a variety of vision and graphics tasks such as relighting, appearance analysis and scene recovery.
机译:作为户外主要观察到的光源,天空是有关场景的丰富信息来源。但是,由于它在图像中的出现取决于太阳的位置,天气条件,相机的光度和几何参数以及拍摄位置,因此在计算机视觉中尚待全面研究。在本文中,我们分析了天空区域可见部分中可用的两种信息来源:太阳位置和天空外观。通过将预测的太阳位置的模型拟合到图像序列,我们展示了如何提取相机参数,例如焦距,天顶和方位角。同样,我们展示了如何通过将基于物理的天空模型拟合到天空外观来提取相同的参数。简而言之,太阳和天空是几何校准目标,可用于注释大型图像序列数据库。我们在已知相机参数的高质量图像序列上测试了我们的方法,对于焦距,方位角为1°,天顶角为3°的误差小于1%。我们还使用我们的方法来校准遍布美国大陆的22个真实的,低质量的网络摄像头序列,并且显示焦距的偏差低于4%,天顶角和方位角的偏差低于3°。最后,我们证明了通过结合太阳位置和天空外观中可用的信息,我们还可以估计摄像机的地理位置及其几何参数。我们的方法在真实的低质量Internet网络摄像头上实现了110 km的平均定位误差。估计的场景观看和照明几何形状可用于各种视觉和图形任务,例如重新照明,外观分析和场景恢复。

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