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Self-calibration of asynchronized camera networks

机译:异步摄像机网络的自校准

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摘要

Calibration of camera networks is a well studied problem. However, most previous attempts assume all the cameras in the network to be synchronized which is especially difficult over large distances. In this paper we present a simple method to fully calibrate the asynchronized cameras of differing frame rates from the acquired video content directly. The presented methods either utilize content based tracked features or alternatively a light marker together with epipolar or homography based constraints to estimate the synchronization as well as intrinsic and extrinsic camera parameters. We assume two cameras within the network to be pre-calibrated (intrinsics only) using standard approaches. We validate our method with numerous simulations for noise analysis as well as real experiments. Furthermore we show how our approach can be used for robust 3D reconstruction in spite of using asynchronized cameras.
机译:摄像机网络的校准是一个经过充分研究的问题。但是,大多数以前的尝试都假定网络中的所有摄像机都要同步,这在长距离情况下尤其困难。在本文中,我们提出了一种简单的方法,可以直接从获取的视频内容中完全校准具有不同帧频的异步摄像机。提出的方法或者利用基于内容的跟踪特征,或者利用光标记以及基于对极或单应性的约束条件来估计同步以及固有和非固有相机参数。我们假设网络中的两个摄像头将使用标准方法进行预校准(仅内部)。我们通过大量用于噪声分析的模拟以及实际实验来验证我们的方法。此外,我们展示了尽管使用了异步相机,我们的方法仍可如何用于强大的3D重建。

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