| 单视图摄像机自标定 |
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| 引用本文： | 杨忠根,张振.单视图摄像机自标定[J].上海海事大学学报,2004,25(4):47-50. |
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| 作者姓名： | 杨忠根 张振 |
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| 作者单位： | 上海海事大学,信息工程学院,上海,200135 |
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| 基金项目： | 上海市高等学校科学技术发展基金项目资助(01G02) |
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| 摘 要： | 首先定义基于模型的单视图情况下的单应性矩阵、外极线约束和基础矩阵,然后通过对基础矩阵的SVD分析,证明使用经其左奇异变换阵变换过的数据集合可最优地估计一个能解析地确定单应性矩阵的四维参数,并进而计算摄像机内参数阵、三维运动参数和目标三维结构,从而开发了一个基于目标模型的从单视图特征点集进行摄像机自标定和三维重建的线性算法。
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| 关 键 词： | 计算机视觉 单视图摄像机自标定 三维重建 单应性矩阵 基础矩阵 |
| 文章编号： | 1672-9498(2004)04-0047-04 |
| 修稿时间： | 2004年3月24日 |
Camera self-calibration for single-view |
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| YANG Zhonggen,ZHANG Zhen.Camera self-calibration for single-view[J].Journal of Shanghai Maritime University,2004,25(4):47-50. |
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| Authors: | YANG Zhonggen ZHANG Zhen |
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| Abstract: | The homographic matrix, epipolar constraint and fundamental matrix in the case of model-based single-view are firstly defined. Then, by means of the SVD analysis of the fundamental matrix, the 4-dimensional parameter vector from which the homographic matrix is analytically and uniquely determined can be optimally estimated from the data transformed by the left singular matrix of the fundamental matrix. At last, the intrinsic parameter matrix, the 3D motion as well as the 3D reconstruction can be straightforwardly calculated from the determined homographic matrix. So, a linear algorithm to self-calibrate the intrinsic parameter matrix of a camera and to reconstruct the 3D shape of the target in the single-view is successfully developed. |
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| Keywords: | computer vision camera calibration for single-view 3D reconstruction homographic matrix fundamental matrix |
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