A new calibration algorithm for multi-camera systems using 1D calibration objects is proposed. The algorithm inte- grates the rank-4 factorization with Zhang (2004)'s method. The intrinsic parameters as well as th...A new calibration algorithm for multi-camera systems using 1D calibration objects is proposed. The algorithm inte- grates the rank-4 factorization with Zhang (2004)'s method. The intrinsic parameters as well as the extrinsic parameters are re- covered by capturing with cameras the 1D object's rotations around a fixed point. The algorithm is based on factorization of the scaled measurement matrix, the projective depth of which is estimated in an analytical equation instead of a recursive form. For more than three points on a 1D object, the approach of our algorithm is to extend the scaled measurement matrix. The obtained parameters are finally refined through the maximum likelihood inference. Simulations and experiments with real images verify that the proposed technique achieves a good trade-off between the intrinsic and extrinsic camera parameters.展开更多
摄像机标定是计算摄像机成像模型参数的过程,它是计算机视觉中的一个基本问题.在分析摄像机成像模型基础上,提出了一种基于OpenCV的摄像机标定技术.该技术采用张氏平面标定原理,并且借助于开源的OpenCV函数库在Visual Studio 2005开发...摄像机标定是计算摄像机成像模型参数的过程,它是计算机视觉中的一个基本问题.在分析摄像机成像模型基础上,提出了一种基于OpenCV的摄像机标定技术.该技术采用张氏平面标定原理,并且借助于开源的OpenCV函数库在Visual Studio 2005开发平台下完成标定.实验结果表明,该标定技术简便而有效,具有较高的标定精度,可以广泛应用于三维重构、虚拟现实等领域.展开更多
基金the National Natural Science Foundation of China (No. 60675017) the National Basic Research Program of China (No. 2006CB303103)
文摘A new calibration algorithm for multi-camera systems using 1D calibration objects is proposed. The algorithm inte- grates the rank-4 factorization with Zhang (2004)'s method. The intrinsic parameters as well as the extrinsic parameters are re- covered by capturing with cameras the 1D object's rotations around a fixed point. The algorithm is based on factorization of the scaled measurement matrix, the projective depth of which is estimated in an analytical equation instead of a recursive form. For more than three points on a 1D object, the approach of our algorithm is to extend the scaled measurement matrix. The obtained parameters are finally refined through the maximum likelihood inference. Simulations and experiments with real images verify that the proposed technique achieves a good trade-off between the intrinsic and extrinsic camera parameters.
文摘摄像机标定是计算摄像机成像模型参数的过程,它是计算机视觉中的一个基本问题.在分析摄像机成像模型基础上,提出了一种基于OpenCV的摄像机标定技术.该技术采用张氏平面标定原理,并且借助于开源的OpenCV函数库在Visual Studio 2005开发平台下完成标定.实验结果表明,该标定技术简便而有效,具有较高的标定精度,可以广泛应用于三维重构、虚拟现实等领域.
