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Camera auto-calibration using pedestrians and zebra-crossings

机译:使用行人和斑马线进行相机自动校准

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In this paper we present a novel camera self-calibration technique to automatically recover intrinsic and extrinsic parameters of a static surveillance camera by observing a traffic scene. The scene must consist of one or more pedestrians and a zebra-crossing. We first extract a horizontal vanishing point and a vanishing line from a zebra-crossing. The observation of pedestrians allows calculating a so called vertical line of mass. All lines of mass are parallel in 3D space and therefore the vertical vanishing point can be estimated. The second horizontal vanishing point can be calculated by introducing the triangle spanned by three orthogonal vanishing points. All three vanishing points are then taken to gather the intrinsic parameters. The extrinsic parameters are calculated after the determination of the camera's height from the distance between two zebra-crossing edges. By combining static and dynamic calibration objects, the method gets robust against outliers. This robustness in combination with the practicability is shown in our experiments, which are carried out by using synthetic and real data of different application scenarios.
机译:在本文中,我们提出了一种新颖的摄像机自校准技术,该技术可以通过观察交通场景自动恢复静态监控摄像机的内在和外在参数。场景必须由一个或多个行人和一个斑马线组成。首先,我们从斑马线上提取水平消失点和消失线。观察行人可以计算出所谓的垂直质量线。所有质量线在3D空间中都是平行的,因此可以估计垂直消失点。可以通过引入由三个正交消失点跨越的三角形来计算第二个水平消失点。然后采用所有三个消失点来收集固有参数。在从两个斑马线边缘之间的距离确定了相机的高度之后,计算外部参数。通过组合静态和动态校准对象,该方法可抵抗异常值。在我们的实验中显示了这种鲁棒性与实用性的结合,这些实验是通过使用不同应用场景的综合数据和真实数据来进行的。

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