An accurate extrinsic camera self-calibration method in non-overlapping camera sensor networks
An accurate extrinsic camera self-calibration method in non-overlapping camera sensor networks
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DOI：
10.1109/imtc.2011.5944093
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发表时间：
2011-05
期刊：
影响因子：
--
通讯作者：
Qiang Wang;Yan Liu;Yi Shen
中科院分区：
文献类型：
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作者：
Qiang Wang;Yan Liu;Yi Shen
摄像机的精确外部自标定，即由摄像机自身确定网络摄像机的位置和方向，在监控、智能环境和交通监控等应用中是必不可少的。本文提出了一种有效的、无测距和无锚点的方法，用于非重叠摄像机传感器网络中摄像机外部参数的自校准。该方法基于Ali在2004年CVPR上提出的方法。从安装在移动对象上的辅助传感器（加速度计或角度加速度计）获得的位置或角度的知识提供了对优化问题的附加有效约束，以便计算相机的姿态。仿真结果表明，改进方法的迭代次数、标定误差、所需数据量均远小于原方法。该方法的优点是，它可以应用，即使当目标需要急转的任何相机的视场（FoV）的小步骤。
Accurately extrinsic camera self-calibration, namely determining the positions and orientations of the networked cameras by themselves, is essential for many applications such as surveillance, intelligent environments and traffic monitoring. This paper describes an efficient, range-free and anchor-free method for self-calibrating the extrinsic parameters of the cameras in a non-overlapping camera sensor networks. The proposed method is based on the method proposed by Ali on the 2004's CVPR. Knowledge of the locations or angles, got from the assisted sensor (accelerometer or angular-accelerometer) installed on the moving object provide additional effective constraints on the optimization problem in order to compute the cameras' poses. Simulation results show that the iteration times, the calibration error, the volume of the data needed by the improved method are far less than the original method. The advantage of the method is that it can be applied even when the target takes sharp turns out of any camera's Field of View (FoV) with little steps.