混合摄像机网络的标定

Xilin Chen, Jie Yang, A. Waibel
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引用次数: 40

摘要

基于摄像机网络的视觉监控对摄像机标定提出了新的挑战。一个重要的问题是,大量的相机可能没有一个共同的视野,甚至不能很好地同步。我们建议使用混合摄像机网络,由反射和透视摄像机组成的视觉监控任务。从不同相机拍摄的场景的多个视图之间的关系可以在反射相机的坐标系下进行校准。我们解决了如何校准混合摄像机网络的重要问题。我们分三步校准混合摄像机网络。首先,我们只使用消失点校准反射相机。为了降低计算复杂度,我们先对无反射镜的摄像机进行标定,然后再对反射镜摄像机系统进行标定。其次,我们使用少至两条空间平行线和一些等距点来确定一些点的三维位置。最后,我们根据这些已知的空间点校准其他透视相机。
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Calibration of a hybrid camera network
Visual surveillance using a camera network has imposed new challenges to camera calibration. An essential problem is that a large number of cameras may not have a common field of view or even be synchronized well. We propose to use a hybrid camera network that consists of catadioptric and perspective cameras for a visual surveillance task. The relations between multiple views of a scene captured from different cameras can be then calibrated under the catadioptric camera's coordinate system. We address the important issue of how to calibrate the hybrid camera network. We calibrate the hybrid camera network in three steps. First, we calibrate the catadioptric camera using only the vanishing points. In order to reduce computational complexity, we calibrate the camera without the mirror first and then calibrate the catadioptric camera system. Second, we determine 3D positions of some points using as few as two spatial parallel lines and some equidistance points. Finally, we calibrate other perspective cameras based on these known spatial points.
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