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首页> 外文会议>Proceedings of the 2016 IEEE National Aerospace and Electronics Conference >Camera principal point estimation from vanishing points
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Camera principal point estimation from vanishing points

机译：从消失点估计相机主要点

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摘要

Calibration is a fundamental task in computer vision and photogrammetry. One of the most important intrinsic camera parameters is the principal point, which is the intersection between the optical axis and the image plane. The proposed method, which uses simple properties of vanishing points, provides a new technique for accurate identification of the principal point. It is done independently of all the other camera parameters. Checkerboard image corner points are located as saddle points, and the Hough transform is applied to remove spurious points and group them into rows and columns. The vanishing point for the columns lie on a horizon line. A group of images, created by rotating the checkerboard while holding the camera stationary, is processed in this manner to create multiple vanishing points on the same horizon line. A perpendicular line to the horizon is then projected back through the principal point. Repeating this for several image groups, corresponding to different camera orientations, allows for accurately locating the principal point as the intersection of the perpendiculars. Our approach does not need any prior information about the cameras being used, and does not require any manual user interaction. Experiments to evaluate the performance of this approach on real test images indicates that the uncertainty for the principal point location overlaps and is smaller than the region found by Bouget's toolbox.
机译：校准是计算机视觉和摄影测量的基本任务。最重要的相机固有参数之一是主点，即光轴与像平面之间的交点。所提出的方法利用了消失点的简单特性，为准确识别主要点提供了一种新技术。它独立于所有其他摄像机参数而完成。棋盘图像的拐角点位于鞍点，并且应用了Hough变换来去除虚假点并将其分组为行和列。列的消失点位于地平线上。以这种方式处理一组图像，这些图像是通过在保持照相机静止不动的同时旋转棋盘格而创建的，以在同一水平线上创建多个消失点。然后，一条垂直于地平线的线通过主点投影回去。对对应于不同相机方向的几个图像组重复此操作，可以准确地将主点定位为垂直线的交点。我们的方法不需要有关所使用摄像机的任何先验信息，也不需要任何手动用户交互。评估此方法在真实测试图像上的性能的实验表明，主要点位置的不确定性重叠并且小于Bouget工具箱发现的区域。

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