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基于自标定的两视图三维重构研究
Research on 3D Reconstruction of Two Views Based on Self-calibration
【摘要】 相机标定是三维重构中的关键步骤,本文对在自标定下的两视图三维几何模型恢复进行研究。先采用SURF算法得到图像匹配点对,在此基础上,利用RANSAC鲁棒估计基础矩阵;然后根据Kruppa方程所推导出的二次方程自标定出相机内参数,进一步地,通过分解本质矩阵求解出相机外参数;最后,根据三角化法求得空间三维坐标值。实验结果证实,该方法具有效性和正确性,并且能够真实地再现物体的三维模型。
【Abstract】 Since camera calibration is a critical step in the three-dimensional reconstruction,the 3D geometric model recovery of two views based on self-calibration is studied in this paper.Firstly,image matching points are obtained by using SURF algorithm,and then fundamental matrix is robustly estimated with RANSAC.Secondly,the intrinsic parameters are calculated according to a quadratic equation which is educed the Kruppa equation;moreover,the external parameters are also solved through SVD decomposition of the essential matrix.Finally,spatial three-dimensional coordinate values are easily obtained by the triangulation method.The experimental results validate the validity and correctness of this method,which can factually represent 3D model of objects.
【Key words】 SURF Algorithm; Fundamental Matrix; Essential Matrix; Self-calibration;
- 【文献出处】 科技广场 ,Science Mosaic , 编辑部邮箱 ,2012年07期
- 【分类号】TP391.41
- 【下载频次】92